Data Platform

Data Platform Jobs

93 jobs found

6d ago

Data Engineer, Deal Intelligence & Automation

Amazon Web Services, Inc. Arlington, VA

Arlington, VA

6d ago

$155k - $209k/yr Full time Analytics Artificial Intelligence Business Analytics

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Job Description

Data Engineer role within AWS GDSP focused on building and maintaining data pipelines, models, and platforms to unlock deal intelligence and automation.

Responsibilities

Develop and sustain the backend data architecture supporting analytical and visualization platforms, ensuring data quality, freshness, and efficient downstream use.
Turn business problems into technical data requirements by partnering with product management and stakeholders to define data products.
Automate and optimize reporting workflows to enable self-service analytics at scale, reducing manual effort and accelerating insights.
Create measurement frameworks and KPIs to quantify deal execution performance and system health.
Monitor, validate, audit, and document pipelines and data sources to ensure data quality.
Leverage AWS services and generative AI to design next-generation data solutions that boost efficiency and unlock new analytical capabilities.

Requirements

5+ years of data engineering experience.
Experience with data modeling, data warehousing, and building ETL pipelines.
Proficiency in SQL.
Experience with at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS.
Experience mentoring team members on best practices.

Technologies

SQL
Python
Java
Scala
NodeJS
Hadoop
Hive
Spark
EMR
AWS services
Generative AI

Benefits

Sign-on payments and RSUs
Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
401(k) matching
Paid time off
Parental leave

About the Team

The team develops products that power how GDSP operates.
Reporting and tooling are built to meet high standards of clarity, reliability, and scalability.

Diverse Experiences

AWS values diverse experiences and encourages applicants to apply even if not all preferred qualifications are met. If your career is nontraditional or just starting, consider applying.

Why AWS

AWS is the world’s most comprehensive and broadly adopted cloud platform, trusted by startups and Global 500 companies for powering their businesses through ongoing innovation.

Inclusive Team Culture

AWS supports curiosity and connection through affinity groups and inclusion events that foster stronger, more collaborative teams and celebrate diverse perspectives.

Mentorship & Career Growth

Continuous opportunities for knowledge sharing, mentorship, and career development resources to help professionals grow.

Work/Life Balance

Emphasis on work-life harmony with flexible work practices to support home and professional responsibilities.

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7d ago

Associate Data Engineer

Baker Tilly Advisory Group, LP Tampa, FL

Tampa, FL

7d ago

$86k - $163k/yr Full time Analytics Azure Azure Data Factory

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Job Description

Associate Data Engineer role in Tampa, FL (onsite) focused on designing, building, and optimizing modern data solutions for mid-market and enterprise clients using the Microsoft stack (Azure, Synapse, Fabric).

Responsibilities

Develop scalable, well documented ETL/ELT pipelines using T-SQL, Python, Azure Data Factory/Fabric Data Pipelines, and Databricks; apply best practice patterns for performance, security, and cost control.
Design relational and lakehouse models; create Fabric OneLake shortcuts, medallion style layers, and dimensional/semantic models for Power BI.
Build automated data quality checks, lineage, and observability metrics; contribute to CI/CD workflows in Azure DevOps or GitHub.
Gather requirements, demo iterative deliverables, document technical designs, and translate complex concepts to non-technical audiences.
Research new capabilities, share findings in internal communities of practice, and contribute to reusable accelerators; collaborate with clients and internal stakeholders to design scalable data engineering solutions.

Requirements

Bachelor's degree in Computer Science, Information Systems, Engineering, or related field (or equivalent experience)
2–3 years delivering production data solutions, preferably in a consulting or client-facing role
Strong T-SQL for data transformation and performance tuning
Python for data wrangling, orchestration, or notebook-based development
Hands-on ETL/ELT with at least one Microsoft service (Azure Data Factory, Synapse Pipelines, Fabric Data Pipelines)
Project experience with Microsoft Fabric (OneLake, Lakehouses, Data Pipelines, Notebooks, Warehouse, Power BI DirectLake) preferred
Familiarity with Databricks, Delta Lake, or comparable lakehouse technologies preferred
Exposure to DevOps (YAML pipelines, Terraform/Bicep) and test automation frameworks preferred
Experience integrating SaaS/ERP sources (e.g., Dynamics 365, Workday, Costpoint) preferred

Technologies

T-SQL
Python
Azure Data Factory
Fabric Data Pipelines
Databricks
Microsoft Fabric
OneLake
Lakehouses
Power BI
Delta Lake
Azure DevOps
GitHub
YAML pipelines
Terraform
Bicep
Dynamics 365
Workday
Costpoint

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7d ago

Data Engineer, Deal Intelligence & Automation

Amazon Web Services, Inc. Santa Monica, CA

Santa Monica, CA

7d ago

$155k - $209k/yr Full time Analytics Artificial Intelligence Big Data

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Job Description

Join Amazon Web Services, Inc. as a Data Engineer within the GDSP group. This onsite role is based in Santa Monica, CA with a compensation range of USD 154,600 to 209,100 per year. You will design, build, and maintain data pipelines, models, and platforms that power deal intelligence and automation across the organization. Partnering with product management and engineering, you will apply AWS services and generative AI to elevate data quality and unlock deeper insights.

Benefits

Sign-on payments
Restricted stock units (RSUs)
Health insurance
401(k) matching
Paid time off
Parental leave
Basic Life & AD&D insurance
EAP
Mental Health Support
Flexible Spending Accounts
Adoption and Surrogacy Reimbursement coverage
Medical Advice Line

Responsibilities

Design and sustain the backend data layer that supports analytics and visualization tools, ensuring data is clean, fresh, and optimized for downstream consumption
Convert business challenges into technical data requirements by collaborating with product management and stakeholders to define data products
Automate and optimize reporting workflows to enable self-service analytics at scale, reducing manual effort and accelerating time to insight
Create measurement frameworks and KPIs to quantify deal execution performance and operational health
Monitor, validate, audit, and document pipelines and data sources to maintain data quality
Leverage AWS services and generative AI to build advanced data solutions that improve efficiency and expand analytical capabilities

Requirements

Minimum of five years of data engineering experience
Experience with data modeling, warehousing, and constructing ETL pipelines
Proficiency in SQL
Experience in at least one modern scripting or programming language such as Python, Java, Scala, or Node.js
Experience mentoring team members on best practices

Technologies

SQL
Python
Java
Scala
NodeJS
Hadoop
Hive
Spark
EMR
AWS services
Generative AI

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7d ago

Data Engineer, OIS/CXI Analytics

Amazon.com Services LLC Nashville, TN

Nashville, TN

7d ago

$126k - $170k/yr Full time Analytics Artificial Intelligence AWS

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Job Description

Data Engineer on the OIS/CXI Analytics team, onsite in Nashville, TN, will build scalable data pipelines and ML-ready data infrastructure to power AI-driven operational insights across Amazon's fulfillment and operations networks; salary range USD 125,500 - 169,800 per year.

Responsibilities

Design, build, and maintain production-grade ETL/ELT pipelines and scalable big data infrastructure that support OTS operational intelligence.
Create feature engineering workflows and ML-ready data pipelines enabling Data Science experimentation and production model serving.
Contribute to data governance and quality standards across analytics and ML data products.
Assist in deploying GenAI solutions for automated reporting, diagnostics, and predictive and prescriptive analytics.
Develop and sustain semantic layers and dashboard data models to drive global operations decisions.
Collaborate with Program Managers, BI teams, ML Engineers, Data Scientists, and operational stakeholders to prioritize work aligned with OTS business goals.
Adhere to and contribute to data engineering best practices, including code reviews, testing, monitoring, and documentation.

Requirements

At least three years of data engineering experience.
A minimum of three years designing and managing large-scale data architectures for BI analytics, supported by data modeling experience.
Proficiency in data modeling, data warehousing, and constructing ETL pipelines.
Experience with AWS services including Redshift, S3, AWS Glue, EMR, Kinesis, Firehose, Lambda, and IAM roles and permissions.
Experience in data warehouse architectures, data modeling, infrastructure components, ETL/ELT processes, reporting/analytics tools and environments, data structures, and hands-on SQL coding.
Bachelor's degree or higher in computer science, engineering, machine learning, or related fields, or equivalent experience building and maintaining data flows and pipelines.
Proficiency in Python and SQL; experience with PySpark or Apache Spark.
Experience with infrastructure-as-code tools such as CDK or CloudFormation, and CI/CD pipelines for data and ML systems.
Experience in data modeling and relational as well as non-relational database design.

Technologies

Python
SQL
PySpark
Apache Spark
Redshift
S3
AWS Glue
EMR
Kinesis
Firehose
Lambda
IAM
CDK
CloudFormation

Benefits

Medical, Dental, and Vision Coverage
Maternity and Parental Leave Options
Paid Time Off (PTO)
401(k) Plan

Preferred Qualifications

Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
Master's degree or above in computer science, engineering, analytics, mathematics, statistics, IT or equivalent

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7d ago

Data Engineer, Finance Data & BI

MCKESSON Richmond, VA

Richmond, VA

7d ago

$107k - $178k/yr Full time Analytics Business Intelligence Cloud

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Job Description

McKesson is seeking a Data Engineer on the Finance Solutions team to design, build, and maintain scalable data pipelines and analytics-ready datasets for Finance Data & BI in a hybrid Richmond, VA role.

Responsibilities

Tackle complex problems across the full data stack, from advanced data wrangling (SQL, Python, Spark, or similar) to delivering stakeholder-ready, production-scale data solutions
Architect new designs and reengineer existing ones, optimizing data structures, relational databases, and database code
Build, test, and maintain robust, scalable ETL/ELT pipelines using modern cloud technologies that support advanced analytics and AI/ML workloads
Develop and maintain database code, including stored procedures, functions, and performance-optimized transformations
Create and sustain ETL processes and contribute to CI/CD deployment workflows using GitHub Actions or similar tools
Implement and optimize data models, including dimensional modeling, within the Finance data environment
Optimize data architecture for performance, scalability, and cost efficiency across large financial datasets
Design automated data quality checks, anomaly detection, and validation processes to ensure accuracy for downstream analytics and AI use cases
Ensure all data solutions meet governance and compliance standards, including SOX requirements
Collaborate with Finance teams (Accounting, FP&A), BI, and Data Product partners to translate complex business needs into scalable technical solutions
Communicate technical concepts clearly to non-technical stakeholders, balancing innovation with operational risk and controls
Enable trusted data environments required for forecasting models, scenario planning, and AI-driven insights
Contribute to the strategic evolution of the Finance data platform by evaluating and piloting emerging tools and technologies

Requirements

4+ years of relevant experience as a Data Engineer
4+ years of hands-on experience with data warehouse solutions, cloud platforms, relational databases, and data visualization or dashboarding tools
4+ years of experience working with structured and unstructured data in batch and real-time data processing environments
Strong proficiency in object-oriented programming languages such as Python, Java, or C#
Demonstrated experience with Google Cloud Platform (GCP) preferred over other platforms (e.g., Snowflake, Databricks, Microsoft, Teradata)
Proven enterprise experience including:
- Building and optimizing cloud-based data solutions
- Supporting business-critical systems
- Designing or supporting production-scale AI/ML data pipelines
- Embedding data governance by design
- Data warehousing and ETL best practices
- CI/CD and version control using GitHub

Technologies

SQL
Python
Spark
Google Cloud Platform (GCP)
GitHub Actions
GitHub
Matillion
PySpark
Oracle JD Edwards
Snowflake
Databricks
Teradata
Java
C#

Benefits

Base pay range: USD 106,500 - 177,500 per yearly
Annual bonus or long-term incentive opportunities may be offered

Hybrid expectations

This position is based in Richmond, VA with 3 to 5 days in the office each month
Preferred candidates must currently reside within a reasonable commuting distance (defined as within 60 miles of Richmond)
Relocation assistance is not available for this role

Compensation

Base: $130,000 to $140,000
10% Annual Incentive

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7d ago

Senior Analytics Engineer, People Data

Anduril Industries Costa Mesa, CA

Costa Mesa, CA

7d ago

$166k - $220k/yr Full time Senior Analytics Apache Airflow

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Job Description

Anduril Industries is seeking a Senior Analytics Engineer focused on People Data to design and maintain the data infrastructure, models, and pipelines that power analytics across HR systems. This onsite role in Costa Mesa, CA centers on turning disparate people data into reliable, accessible insights to support data-driven decisions within the People organization. The position offers a salary range of USD 166,000 to 220,000 per year and requires a strong background in data engineering to scale our analytics capabilities.

Responsibilities

Design, build, and optimize robust ETL/ELT pipelines to reliably ingest, integrate, and transform diverse people data from various HR systems (HRIS, ATS, LMS, etc.) into our data platform.
Develop, maintain, and govern scalable and secure data models, schemas, and ontologies specifically for people analytics, ensuring data quality, consistency, and accessibility for downstream consumption.
Contribute to the strategic design, development, and evolution of our people data platform and tooling, advocating for engineering best practices, automation, and a scalable analytics ecosystem (e.g., leveraging SQLMesh, Iceberg, Flyte).
Partner closely with People Analysts, HR Business Partners, and other stakeholders to understand their analytical needs and translate them into robust data solutions, providing well-structured, documented, and reliable datasets.
Implement and monitor data quality checks, identify discrepancies, troubleshoot data issues, and ensure the reliability and integrity of people data across all systems.
Continuously monitor the performance of data pipelines and models, identifying bottlenecks and implementing solutions to ensure the efficiency and scalability of our people data infrastructure.
Create and maintain comprehensive documentation for data pipelines, models, and processes, and champion data engineering best practices (e.g., version control, testing, CI/CD) within the team.
Implement and enforce strict data security measures and ensure all data handling practices comply with internal policies and external regulations (e.g., GDPR, CCPA) related to employee data privacy.
Collaborate with broader enterprise analytics and data engineering teams to align on data architecture standards, integrate people data with other business domains, and contribute to the overall evolution of the company's data platform.

Requirements

5+ years of progressive experience in Data Engineering, Analytics Engineering, or a similar role focused on building and optimizing data pipelines and data infrastructure.
Expert-level proficiency in SQL for complex data manipulation and querying, and advanced Python for scripting, data processing, and automation.
Extensive experience with cloud-based data warehousing solutions (e.g., Snowflake, Google BigQuery, AWS Redshift, Databricks/Delta Lake) and data lake technologies (e.g., AWS S3, Azure Data Lake Storage).
Deep understanding and proven experience in designing, implementing, and maintaining robust data models (e.g., dimensional modeling, Kimball methodology) for analytical purposes.
Hands-on experience building and optimizing complex ETL/ELT processes and data pipelines using modern tools such as dbt, Apache Airflow, Flyte, Dagster, or similar orchestration platforms.
Excellent communication skills, both written and verbal, with the ability to translate technical concepts for non-technical stakeholders and collaborate effectively across diverse teams.
Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field.
Strong technical foundation in data engineering, with expertise in SQL, Python, and experience working with cloud-based data platforms (AWS, GCP, Azure).

Technologies

SQL, Python
Snowflake
Google BigQuery
AWS Redshift
Databricks/Delta Lake
AWS S3
Azure Data Lake Storage
dbt
Apache Airflow
Flyte
Dagster
Iceberg
SQLMesh
Palantir Foundry
Terraform
CloudFormation
Docker
Kubernetes
Tableau
Power BI
Looker
Rippling
Workday
Oracle HCM Cloud
Apache Spark
Flink

Benefits

Equity grants included in the majority of full-time offers and are part of total compensation
Comprehensive benefits package for full-time employees, including health and recovery support

Preferred Qualifications

Experience with big data processing frameworks (e.g., Apache Spark, Flink) and advanced data warehousing features like schema evolution or time travel (e.g., Iceberg, Delta Lake).
Direct hands-on experience with tools mentioned in our stack like Palantir Foundry, SQLMesh, Flyte, or similar cutting-edge data orchestration and transformation platforms.
Relevant professional certifications from major cloud providers (e.g., AWS Certified Data Analytics - Specialty, Google Cloud Professional Data Engineer).
Experience with Terraform, CloudFormation, Docker, or Kubernetes for managing data infrastructure and deploying applications.
Familiarity with integrating data pipelines with leading BI tools (Tableau, Power BI, Looker) to optimize dashboard performance and data accessibility for end-users.
Deep expertise working with data from specific enterprise HRIS systems like Rippling, Workday, and Oracle HCM Cloud including their data models and APIs.
Solid understanding of HR data concepts, metrics, and common HR systems (HRIS, ATS, LMS), with a strong interest in People Analytics.

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7d ago

Senior Data Analyst - Deposits

Bank OZK Little Rock, AR

Little Rock, AR

7d ago

Full time Analyst Analytical Skills Analytics

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Job Description

This is an on site role in Little Rock, Arkansas. The Senior Data Analyst - Deposits serves as the primary deposits data expert at Bank OZK, guiding pricing, campaign analytics, and product insights while partnering with technology teams to elevate the Deposit Management data capabilities.

Responsibilities

Examines product, customer, pricing, financial, sales, and deposit data to identify trends and derive actionable insights.
Collaborates with technology partners to build and enhance the Deposit Management team's data capabilities.
Interprets analyses and recommends measures to improve performance and profitability.
Leads ongoing and ad hoc analytical initiatives for the Deposit Management team.
Conducts research across the Bank's broad range of products and services.
Assesses pricing experiments to gauge customer response to various initiatives and strategies.
Develops ongoing reports to monitor the performance of deposit portfolios.
Collaborates with multiple teams to coordinate report distribution and share insights with stakeholders, including executive decision-makers.
Presents findings and analyses to working groups, councils, committees, and executive management as required.
Regularly exercises professional judgment and discretion in performing core duties.
Maintains reliable attendance and punctuality.
Adheres to Bank policies, procedures, and guidelines.

Requirements

A bachelor’s degree in finance, marketing, economics, business, computer science, statistics, or a related field, or equivalent work experience, is required.
At least five years of analytics experience using SQL and common scripting languages such as R or Python, in professional or academic settings.

Technologies

Power BI
Snowflake
SQL
R
Python
Microsoft Word
Microsoft Excel
Microsoft PowerPoint

Benefits

Generous PTO
401(k) matching
Health insurance
Dental insurance
Vision insurance
Pet insurance
Special perks and discounts

Job Purpose & Scope

Provides leadership as the principal deposits data expert across the organization, delivering guidance on deposit pricing, campaign and marketing initiatives, customer and product analytics, and sales reporting requirements.