Analytics Engineer

Analytics Engineer Data Jobs

9 jobs found

Today

Analytics Engineer

Pacific Life Insurance Company Newport Beach, CA

Newport Beach, CA

Today

$103k - $126k/yr Full time Analytics Engineer Artificial Intelligence Azure DevOps

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Job Description

Pacific Life Insurance Company is hiring an Analytics Engineer to turn enterprise data into trusted, reusable analytics products for reporting and AI use cases.

Responsibilities

Develop and maintain modular SQL transformations and analytical data models using dbt and Snowflake, delivering reusable datasets for reporting, analysis, data science, and AI.
Collaborate with business and technical stakeholders to translate needs into data definitions, business rules, metrics, and semantic models.
Document relationships and assumptions so data can be interpreted consistently across teams and use cases.
Build automated tests, validate business logic, investigate discrepancies, and maintain documentation and lineage to support accuracy, clarity, and reliability.
Support development, testing, and evaluation of Snowflake Cortex solutions and AI agents using trusted enterprise data and business context.
Use Git, Azure DevOps (ADO), and CI/CD workflows for pull-request collaboration, automated validation, and controlled releases across development and production.
Apply approved AI development tools, including Claude Code and GitHub Copilot, for development, testing, documentation, and workflow automation.
Review and validate AI-generated outputs while adhering to engineering, privacy, and security standards.
Provide hands-on guidance, demonstrations, documentation, and knowledge transfer so business partners can adopt analytics products and use Snowflake Cortex more independently.
Troubleshoot analytical models and workflows, improve query performance and efficiency, modernize manual processes, and contribute reusable patterns to the team’s engineering playbook.
Partner with data engineering, platform, governance, and technology teams to deliver solutions aligned to enterprise architecture, access controls, and operational standards (including AWS-based components where applicable).

Requirements

Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Mathematics, Engineering, or a related field, or equivalent practical experience.
Typically at least 2–5 years of professional experience in analytics engineering, data engineering, business intelligence development, or a related technical role (minimum 2 years).
Hands-on experience with dbt and Snowflake, including developing, testing, documenting, and maintaining analytical data models.
Strong SQL skills and practical understanding of relational and dimensional modeling, data transformation, business logic, and query optimization.
Experience with Git, branching, pull requests, code reviews, automated testing, and CI/CD.
Experience with Azure DevOps (ADO) or a comparable delivery platform.
Working knowledge of Python for scripting, automation, or data-related development.
Familiarity with AWS and cloud-based data environments; professional AWS experience preferred.
Ability to translate business questions into technical requirements and clearly communicate technical concepts so stakeholders can adopt analytics solutions.
Detail-oriented approach to troubleshooting, validating results, documenting decisions, and following work through delivery.
Preferred: experience with Snowflake Cortex, AI agents, or generative AI solutions.
Plus: familiarity with Claude Code, GitHub Copilot, or other AI-assisted/agentic tools, with willingness to learn and apply them responsibly.
Preferred: experience in insurance, financial services, or another regulated environment (not required).

Technologies

dbt
Snowflake
Snowflake Cortex
AWS
Python
Git
Azure DevOps (ADO)
CI/CD
Claude Code
GitHub Copilot

Location & Compensation

Location: Newport Beach, CA (onsite)
Salary: USD 103,140 - 126,060 per year

Benefits

Medical, Dental, Vision
Wellbeing Reimbursement Account
Paid Time Off
Holiday Schedules
Financial Planning Time Off
Paid Parental Leave
Adoption Assistance Program
401k savings plan with company match
Additional contribution regardless of participation

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2d ago

Analytics Engineer

Koch Engineered Solutions Wichita, KS

Wichita, KS

2d ago

Full time Analytics Engineer Business Analytics Business Intelligence

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Job Description

As an Analytics Engineer at Koch Engineered Solutions in Wichita, KS, you will design and deliver semantic models and BI solutions that support reliable, AI-ready analytics. You will work with analysts, business partners, and data engineering teams to convert raw data into trusted, reusable assets for decision-making.

Responsibilities

Collaborate with analysts and business stakeholders to understand data gaps, define metrics, and design robust, scalable analytics solutions, including proposing alternative approaches with clear pros and cons.
Design and build dimensional models that are clean, performant, and straightforward for end users.
Develop and optimize SQL transformations that convert raw inputs into business-friendly, reusable dimensional model objects.
Create and maintain semantic models that support clear, efficient self-service analytics.
Develop and maintain enterprise Power BI reports and dashboards with attention to usability, performance, and consistent business definitions.
Apply professional development practices such as Git-based version control, branching and pull request workflows, testing and validation, and CI/CD.
Coordinate with data engineers, architects, and other analytics engineers to align on standards for naming, documentation, data quality, and model governance.
Support adoption through documentation of models and metrics, stakeholder training enablement, and improved discoverability.
Troubleshoot data issues across models and reports, and continuously improve reliability and performance.

Requirements

Demonstrated SQL skills for data transformation.
Demonstrated experience building dimensional data models for BI applications.
Hands-on experience with Power BI semantic model and report development.
Experience with Power Query (M), including understanding when and how to use it effectively.
Experience using Git in a team environment, including branches, pull requests, and code reviews.

Technologies

SQL
Dimensional modeling
Power BI
Power Query (M)
Git
CI/CD
Git-based version control
Branching/PR workflows

Benefits

Medical
Dental
Vision
Flexible spending and health savings accounts
Life insurance
ADD
Disability
Retirement
Paid vacation/time off
Educational assistance
May also include infertility assistance
Paid parental leave and adoption assistance

What Will Put You Ahead

Deep knowledge of dimensional modeling best practices and optimization techniques.
Experience with dbt, including models, tests, documentation, macros, and exposures.
Experience collaborating with a Finance team or in the Financial Services industry.
Experience using Snowflake for SQL-based pipelines and reusable model layers.
Experience designing reusable semantic standards for enterprise reporting.
Experience enabling AI-capable models through strong metadata, consistent definitions, curated semantic layers, and documentation.

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5d ago

Analytics Engineer

Primary Talent Partners Indianapolis, IN

Indianapolis, IN

5d ago

$60 - $70/hr Contract Analytics Analytics Engineer Business Analytics

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Job Description

This contract Analytics Engineer role supports operational and analytical foundations for pharmacy dispensing and fulfillment activities within a HIPAA covered-entity environment. The position focuses on building and maintaining metrics, dashboards, and reporting views, while performing SQL and Excel analyses and handling PHI in compliance with HIPAA and established data governance.

Location and Employment Details

Location: Indianapolis, IN (onsite)
Job Type: contract
Compensation: USD 60–70 per hour
Minimum Experience: 1 year

Responsibilities

Support recreation, validation, and maintenance of operational metrics derived from platform usage and pharmacy fulfillment data to improve automation, accuracy, and quality
Ensure data availability, quality, and compliance across dispensing-related workstreams
Create and deploy operational dashboards for use within the Covered Entity
Track and report performance metrics for stakeholders, ensuring timely and accurate updates to reporting tools
Contribute to consolidated cross-source dispensing and reporting views, including filtering, grouping, and finance reporting needs
Perform analyses using SQL and Excel to measure operational performance and identify trends or opportunities
Translate data into clear, actionable insights for internal stakeholders
Support issue resolution through data-driven problem-solving and cross-functional collaboration, including urgent operational challenges
Contribute to KPI and data-strategy documentation
Handle PHI and other sensitive data strictly in accordance with HIPAA, covered-entity policies, and established data-governance guidance
Maintain manufacturer versus covered-entity data separation requirements, especially for partner-level and patient-level data

Requirements

Education: Bachelor’s degree in business, marketing, healthcare administration, data science, or a related discipline
Technical skills: Proficiency in SQL and Excel, plus at least one statistical programming language (Python or R)
Domain familiarity: Knowledge of healthcare, pharmacy, or claims/dispensing operational data
Experience: 1–3 years of work experience in a HIPAA covered entity delivering analytics and insights for CE Operations
Compliance: Ability to complete and maintain required data privacy, HIPAA, and covered-entity compliance training, and to handle protected health information (PHI) per established policies

Technologies

SQL
Excel
Python
R

Benefits

Employment: W2 contract
PTO: no PTO
Benefits: no benefits
Coverage option: ACA-compliant supplemental package available for enrollment

Preferred Qualifications

Strong analytical skills with attention to detail and business acumen
Experience working in Databricks
Excellent communication skills, including simplifying complex concepts
Ability to work cross-functionally and influence without direct authority
High learning agility and adaptability in ambiguous environments
Working understanding of HIPAA/PHI handling and data-governance constraints, including manufacturer versus covered-entity data separation

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6d ago

Analytics Engineer

SBA Network Services, LLC Boca Raton, FL

Boca Raton, FL

6d ago

Full time Analytics Engineer Azure Azure Data Factory

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Job Description

Boca Raton, FL onsite role focused on building governed analytics and AI-ready data products.

Responsibilities

Design, build, and maintain semantic models and curated datasets that turn business logic into reusable, governed data products for self-service analytics and AI consumption.
Develop and optimize data pipelines and dataflows for scalable, performant analytics across Microsoft Fabric, Power BI, Azure, and Databricks.
Prepare clean, structured datasets for AI Agentic workflows.
Partner with citizen developers and business stakeholders to confirm analytical requirements and ensure semantic models meet usability, accuracy, and compliance expectations.
Implement and manage row-level security (RLS) within semantic models to support authorized data access and organizational policy compliance.
Create and run testing and validation strategies to verify accuracy, reliability, and consistency of transformations and analytics outputs.
Use analytics engineering best practices including modular design, version control, and code documentation.
Document business logic, data transformations, and model structures using technical documentation, data dictionaries, and metadata catalogs, supporting data lineage and feature clarity for generative AI and predictive modeling.
Design and implement automated workflow and orchestration strategies to streamline model deployment and ensure timely, reliable data availability.
Coordinate with contractors and internal teams on data architecture, modeling standards, and delivery timelines.
Support adoption of self-service analytics by enabling business users and ensuring data products are intuitive, well-documented, and aligned to user needs.
Other duties as required.

Requirements

Bachelor’s or Master’s degree in Data Engineering, Computer Science, Information Systems, a related field, or equivalent experience.
Minimum 3 years of experience in analytics engineering, data modeling, or business intelligence development.
Advanced proficiency in SQL, DAX, and Power BI, including experience building and optimizing semantic models and dataflows.
Hands-on experience with Microsoft Fabric and modern data architecture principles.
Strong understanding of data governance, row-level security (RLS), and metadata management.
Familiarity with CI/CD pipelines, version control systems (example: Git), and data orchestration tools (example: Azure Data Factory, dbt, or similar).
Proven ability to translate complex business logic into scalable, reusable data products.
Excellent communication skills and the ability to collaborate with both technical and non-technical stakeholders.

Technologies

SQL, DAX, Power BI
Microsoft Fabric, Azure, Databricks
Git
Azure Data Factory, dbt
CI/CD

Benefits

401(k) retirement savings plan with a company match of a percentage of employee contributions and profit sharing, where applicable
Equity opportunities, including participation in company equity stock plans, where applicable
Medical, dental, and vision insurance with employer contributions toward coverage
Paid parental leave and company-paid life insurance and short-term and long-term disability (STD/LTD), where eligible
Wellness programs and resources, including an employee assistance program and well-being initiatives
Paid time off and company-paid holidays
Flexible work arrangements, including an allotment of remote workdays per year, depending on the role
Education assistance and professional development and certification or licensing support, where eligible
Performance-based bonus or incentive compensation, which may be available depending on the role

Physical Demands

Ability to stoop, bend, kneel or crouch.
Ability to stand, walk and sit.
Ability to reach with hands and arms.
Visual ability correctable to 20/20.
Sitting up to 90% of the day.
Ability to respond verbally in an understandable, professional manner in person and over the telephone.
Manual dexterity to input data into the computer and the calculator and operate the equipment listed above.
Ability to lift up to 15 pounds.

Work Environment

Office / cubicle workspace
Moderate noise level

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6d ago

Analytics Engineer

Cracker Barrel Old Country Store Lebanon, TN

Lebanon, TN

6d ago

Full time Analytics Analytics Engineer Analytics Engineering

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Job Description

Join a data-focused team at Cracker Barrel Old Country Store in Lebanon, TN (onsite), where you will build governed analytics that power enterprise reporting, Power BI semantic models, and certified AI use cases. In this Analytics Engineer role, you will design and maintain Snowflake-backed datasets using dbt, while collaborating with business and technical partners to turn KPI definitions into reliable, reusable metric logic.

What you will do

Design, develop, test, deploy, and maintain dbt models in Snowflake.
Transform curated source data into reusable analytical datasets and business-ready data products.
Build dimensional models, including fact and dimension tables, conformed dimensions, hierarchies, and documented grain.
Develop and support Gold-layer models optimized for enterprise reporting, analytics, and approved AI use cases.
Ensure models follow established architecture, naming, SQL, data modeling, security, and documentation standards.
Partner with stakeholders and analysts to translate approved KPI definitions and business rules into governed metric calculations.
Build and maintain curated datasets that support Power BI semantic models, certified data sources, and self-service reporting.
Support metric and data-product certification by documenting technical logic, source fields, lineage, dependencies, refresh expectations, and known limitations.
Create automated dbt tests and validation controls for uniqueness, completeness, accepted values, referential integrity, freshness, and business rules.
Monitor production analytical data products and troubleshoot transformation failures, anomalies, performance concerns, and unexpected reporting results.
Use GitHub and source-control practices to manage branches, submit pull requests, participate in code reviews, and support controlled deployments.
Contribute to CI/CD practices, reusable development patterns, technical templates, and team documentation.
Collaborate with Data Engineering on upstream dependencies, data availability, scalability, and production support needs.
Participate in requirements discovery, solution design, user acceptance testing, and release validation.
Provide guidance to analysts and report developers on certified datasets, model usage, metric logic, and data limitations.
Support training and enablement related to dbt models, governed data products, and certified semantic datasets.
Perform other duties as assigned to support data and analytics initiatives.

What you bring

Bachelor’s Degree in Computer Science, Information Systems, Data Analytics, Mathematics, Statistics, Engineering, or a related field, or an equivalent combination of education, certification, and relevant work experience.
4+ years of experience in analytics engineering, business intelligence, data warehousing, data engineering, or advanced analytics.
3+ years of advanced SQL development experience.
Experience developing analytical solutions within a cloud-based data platform.
Experience with dimensional data modeling and data warehouse concepts.
Ability to translate business and reporting requirements into scalable technical data solutions.
Experience collaborating across technical and business teams.
Advanced SQL problem-solving skills and strong knowledge of relational data structures, transformation, dimensional modeling, and data warehousing concepts.
Working knowledge of dbt development, testing, documentation, dependency management, and deployment practices.
Ability to translate business definitions into consistent, reusable, and testable technical logic.
Knowledge of data quality controls, source control, peer review, and production support practices.
Ability to troubleshoot complex transformation logic and identify root causes across data dependencies.
Strong attention to documentation, naming conventions, standards, and repeatable processes.
Clear written and verbal communication skills and the ability to work with both technical and non-technical stakeholders.
Ability to manage solutions through design, development, validation, deployment, and support.
Commitment to continuous learning and improvement of analytics engineering practices.

Tools you will use

dbt, Snowflake, SQL, GitHub, Power BI, CI/CD

Benefits

Competitive Annual Salary and Annual Bonus Opportunities
Medical, Rx, Dental and Vision benefits on Day 1
Life Insurance and Disability Coverage
Paid Vacation and an Employee Assistance Program
Business Resource Groups
Tuition Reimbursement
Professional Development
Support starts on day one with onboarding, training, and development
Recognition programs and employee events
401k Plan with company matching contributions at 90 days
Employee Stock Purchase Program
35% Discount on Cracker Barrel food and retail items
Exclusive Biscuit Perks including discounts on home, travel, cell phones, and more

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10d ago

Senior BI & Analytics Engineer

SPN Solutions Inc. Fairfax, VA

Fairfax, VA

10d ago

Full time Senior Analytics Analytics Engineer

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Job Description

SPN Solutions Inc. is seeking a Senior BI & Analytics Engineer to support a federal agency’s attorneys, field offices, and program staff with dashboards and AI-assisted views built for everyday decisions. This role focuses on translating agreed requirements into governed, tested data products that the agency accepts and uses, with strict reconciliation to trusted counts and accessibility validated for real users.

What you will do

Lead time-boxed working sessions with each office and the agency’s data and CIO staff to align on decisions and data expectations.
Define every product, including the decision it supports, the grain, the system of record, inclusion rules, who can view it, and an example that demonstrates correctness.
Develop dbt models using declared grain and tests for uniqueness, non-null keys, referential integrity, and accepted values.
Create scheduled extracts that publish only after the full expected volume lands.
Reconcile every released figure to a count the office already trusts before publishing.
Build Apache Superset datasets over dbt models only (no ad hoc SQL), then create dashboards and AI-assisted views on top.
Run acceptance testing with office users, including reconciliation checks, citation accessibility, and validation that restricted roles see only what they should.
Ensure keyboard-accessible interfaces, pair charts with data tables, and validate that meaning is not conveyed by color alone, including contrast checks and screen reader testing.
Produce an onboarding playbook, user and administrator documentation, and deliver enablement sessions.
Document each pipeline end-to-end: source, schedule, dependencies, failure behavior, and owner.

Required qualifications

United States citizenship, with the ability to obtain a Public Trust Tier 2 determination.
5+ years experience across data engineering and business intelligence.
Advanced SQL.
Python with pandas.
Production experience with Power BI, Tableau, Looker, or Apache Superset.
Git.
Demonstrated ability to build for non-technical users and drive adoption.

Technologies and tools

dbt, Apache Superset, PostgreSQL
Python, pandas
Power BI, Tableau, Looker
Git, Apache Superset datasets
Accessibility and testing tools: NVDA, JAWS, ANDI, axe, screen reader testing, and contrast analysis
PIV, PostgreSQL read replica

Work environment

A governed PostgreSQL read replica of the agency’s case system.
The agency’s dbt project for model and test development.
Apache Superset with a developer role in dev and test.
A data catalog where every curated dataset is registered.
Agency Git repositories with CI/CD practices, with work committed from day one.
Python with pandas and visualization libraries for reconciliation and analysis.
Accessibility tooling including screen readers such as NVDA or JAWS, contrast analyzers, ANDI or axe.

First 90 days

Days 1–30: Suitability forms filed on day one; ramp with the Architect for Superset; working-session kit built; first office discovery held.
Days 31–60: First office definition approved by the agency; dbt models with tests built in dev; second office discovery scheduled.
Days 61–90: First Superset product in dev with AI features embedded and reconciled to the office’s control count; accessibility checks passing; acceptance script ready for month 4.

How success is measured

The first product accepted and actively used by month 7, with one for each office by month 10.
Every released figure reconciles to its control count.
Every product passes all four acceptance confirmations.
Adoption materials delivered by month 9 and used by agency staff by month 11.

Benefits

Medical and prescription coverage
Dental and vision
Short-term disability
Life and accidental death insurance
Competitive 401(k)
11 paid federal holidays
Paid vacation
Paid sick leave
Parental leave
Tuition and professional development assistance

Position details

Location: Fairfax, VA (hybrid)
Employment: Full time, W-2, salaried (exempt), employed by SPN Solutions
Target start: 19 October 2026
Scheduling: Hybrid with some days in Washington, DC when needed; living in the Washington, DC area is preferred.
Customer work uses a government-furnished laptop with a PIV credential.
DHS Trusted Tester training is required in month 2 or 3 if not already held, and the training is free.
If coming from Power BI, Tableau, or Looker, the first two to four weeks include a Superset ramp with the Architect.
Apply through the link with your resume.
A recruiter reads every application and responds within two business days.

Application prompt

Include two or three lines about one product you built that non-technical users relied on, and how you verified the numbers were correct.

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12d ago

Analytics Engineer, Integrity

NBA New York, NY

New York, NY

12d ago

$130k - $150k/yr Full time Analytics Engineer Analytics Engineering Azure DevOps

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Job Description

The NBA’s Basketball Strategy & Growth department is hiring an Analytics Engineer for the Integrity Team, working on data that supports the league’s gaming policy. This role focuses on building production-ready datasets by bringing together external betting and OSINT feeds with internal basketball data, enabling anomaly detection, alerting, and AI-driven capabilities under legal scrutiny.

What you’ll do

Own ingestion from betting partners, operators, and data vendors, then normalize their varying schemas, granularity, delivery cadence, and quirks into a consistent, conformed model of markets, wagers, prices, and accounts.
Build and maintain ingestion pipelines for OSINT and other unstructured or semi-structured sources, including entity resolution to link external identities to known accounts and subjects.
Integrate betting and OSINT data with internal league basketball datasets including schedule, play-by-play, box score, tracking, officiating, and player availability so activity can be analyzed in the context of games.
Develop production analytical data models in dbt on Snowflake using dimensional modeling and analytics engineering best practices such as layered staging and mart designs, incremental models, and consistent naming conventions.
Create curated, reusable pipelines and feature-ready datasets for downstream data science and machine learning, including model development, backtesting, and production inference.
Implement automated data quality testing along with freshness and volume monitoring and reconciliation checks so vendor changes, outages, or silent data loss are detected before investigative outputs are impacted.
Design orchestration and scheduling for pipelines, including dependency management, retries, alerting, and service levels for time-sensitive feeds.
Maintain a semantic layer with standardized business definitions and metrics so analysts, data scientists, and the Legal department can rely on a single version of the truth.
Document models, sources, lineage, and assumptions to support knowledge transfer, auditability, and evidentiary needs.
Onboard new betting partners and data providers by evaluating feed quality, defining requirements and specifications, and absorbing schema changes without breaking downstream consumers.
Partner with data scientists to translate analytical and modeling requirements into scalable data models, and with full stack engineering to expose datasets for backend jobs and the UI.
Apply appropriate access controls, data classification, and retention practices for sensitive betting, personal, and investigative data.

What you bring

Advanced SQL with experience building complex analytical data models.
Production experience with dbt, including testing, documentation, macros, and managing a large model DAG.
Production experience with Snowflake, including performance and cost management (warehouse sizing, clustering, and query tuning).
Strong understanding of dimensional modeling, data warehousing, and analytics engineering best practices.
Understanding of sports betting markets (odds, line movement, limits, player props, market maker behavior) and familiarity with basketball data such as play-by-play, box score, and tracking.
Python proficiency for ingestion, API integration, and data processing.
Experience integrating multiple external partners or vendors, including messy, high-volume, semi-structured, and unstructured sources.
Experience operating orchestrated data pipelines with scheduling, dependency management, retries, and monitoring.
Experience building semantic layers, standardized definitions, and reusable analytical datasets.
Experience implementing automated data quality testing, monitoring, and documentation to support trusted analytics.
Experience building pipelines that serve downstream data science and machine learning consumers.
Familiarity with Git-based workflows (GitHub or Azure DevOps), code review, and CI practices.
Strong communication and stakeholder management skills, including translating business and investigative requirements for both technical and non-technical audiences such as attorneys and investigators.
Sound judgment and discretion for handling confidential, legally sensitive information.
Ability to work independently in a fast-paced environment while balancing short-term deliverables with long-term initiatives.
Strong teamwork and cross-functional collaboration within BSG Integrity and beyond.

Technology stack

SQL, dbt, Snowflake, Python, GitHub, Azure DevOps

Preferred skills

Experience with Databricks (Spark, Delta Lake, Unity Catalog) and/or ML lifecycle tooling such as MLflow.
Experience with orchestration tools such as Airflow, Dagster, or Prefect.
Experience with entity resolution, identity matching, or record linkage.
Familiarity with MLOps practices including feature pipelines, model registries, training/retraining workflows, and model monitoring.
Experience in integrity, surveillance, fraud, AML, or trust and safety data is a plus.
Experience in sports, gaming, or other regulated or compliance-driven environments is a plus.

Education and experience

Bachelor’s degree required in a technical or quantitative field (master’s degree preferred).
Minimum 5 years experience in analytics engineering, data engineering, or developing analytical data models on cloud-based platforms.

Location and work option

New York, NY (hybrid)
The NBA provides eligible employees the option of working remotely one day per week.

Compensation

USD 130,000 - 150,000 per year

Benefits

Annual discretionary performance bonus, at the Company’s sole discretion and subject to Company terms and conditions
Medical, dental, and vision
Life/AD&D insurance
Short- and long-term disability
Fertility and family-forming assistance
Wellbeing allowance
Educational assistance
Mental health coaching/therapy
Tax advantaged accounts such as HSA and healthcare/dependent care FSAs
401(k) retirement plan
Vacation, sick time, and personal days

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14d ago

Analytics Engineer

Welldoc Inc Columbia, MD

Columbia, MD

14d ago

$110k - $130k/yr Full time Analytics Analytics Engineer Artificial Intelligence

16d ago

Principal Analytics Engineer

adMarketplace New York, NY

New York, NY

16d ago

$220k - $260k/yr Full time Analytics Analytics Engineer Artificial Intelligence

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