Automation Developer

Automation Developer Data Jobs

93 jobs found

Today

Lead Product AI Data Engineer

DR Decisions Resources LLC Ann Arbor, MI

Ann Arbor, MI

Today

Full time Manager Analytics Artificial Intelligence

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Job Description

The Lead Product AI Data Engineer will define, build, and scale enterprise-grade AI-ready data platforms for the Life Sciences and Healthcare ecosystem, combining data engineering and dimensional modeling with enterprise architecture leadership.

Responsibilities

Define and evolve enterprise-level product data architecture across multiple product lines, ensuring scalability, reliability, and AI/ML readiness.
Architect scalable ETL/ELT pipelines and distributed data workflows for analytics, AI, and product intelligence.
Develop and enforce dimensional data modeling standards, including star schemas and snowflake schemas.
Design and maintain fact and dimension tables, covering proper grain, SCD handling, hierarchical dimensions, and high-performance query patterns.
Establish data architecture principles, including naming conventions and best practices for ETL/ELT, event tracking, and AI pipelines.
Act as the technical authority to guide architecture decisions that meet product, platform, and AI requirements.
Partner with cross-functional teams to translate requirements into scalable, analytics- and AI-ready data models and pipelines.
Curate and validate datasets for machine learning, experimentation, and advanced analytics.
Evolve event-driven architectures to align with dimensional modeling and downstream analytics.
Establish feature store frameworks and reusable AI data pipelines across multiple products.

Requirements

10+ years of professional experience in Data Engineering, Analytics Engineering, or Data Architecture.
Proven experience in enterprise-scale data architecture and distributed pipeline design.
Expert-level proficiency in SQL and relational database design.
Strong hands-on experience in Python for pipeline automation, orchestration, and data framework development.
Deep expertise in dimensional modeling, including star and snowflake schemas, fact/dimension tables, SCDs, surrogate keys, and hierarchical dimensions.
Experience designing and operating production-grade ETL/ELT pipelines for analytics and AI/ML workloads, with the ability to influence technical outcomes through architectural leadership and enterprise strategy.
Experience with cloud data warehouses: Snowflake, Databricks, BigQuery.
Familiarity with modern orchestration and transformation tools: dbt, Airflow, Fivetran, Segment.
Experience handling semi-structured and event-driven data, including JSON, logs, and clickstream.
Exposure to BI and visualization tools: Power BI, Tableau, Looker, SAP BusinessObjects.
Experience with AWS, Azure, or GCP, including data governance, security, and compliance frameworks.
Background in Life Sciences or Healthcare analytics.

Technologies

SQL, Python, Snowflake, Databricks, BigQuery, dbt, Airflow, Fivetran, Segment, JSON, Power BI, Tableau, Looker, SAP BusinessObjects, AWS, Azure, GCP, ETL/ELT, Machine learning, AI/ML, SCDs, star schemas, snowflake schemas, fact/dimension tables, surrogate keys, hierarchical dimensions.

AI and Product Data Enablement

Partner with cross-functional teams to translate requirements into highly scalable, analytics- and AI-ready data models and pipelines.
Curate and validate datasets for machine learning, experimentation, and advanced analytics.
Evolve event-driven architectures to align with dimensional modeling and downstream analytics.
Establish feature store frameworks and reusable AI data pipelines across multiple products.

Location

Ann Arbor, MI (onsite)

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Today

Data Scientist

US District of Columbia Courts Washington, DC

Washington, DC

Today

$118k - $153k/yr Full time Analytics Artificial Intelligence Automation Developer

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Job Description

Data Scientist opportunity with the District of Columbia Courts in the Strategic Management Division in Washington, DC.

Responsibilities

Develop computational algorithms and statistical methods to discover patterns and relationships across multiple database sources.
Develop, manipulate, and manage scripts, queries, and software code to meet specific technical requirements.
Design, build, and test data models, algorithms, and predictive models.
Apply predictive modeling and machine learning techniques to strengthen program and operational processes and improve agency data quality.
Generate data-driven insights that support evidence-based process and operational recommendations for the Courts and stakeholders.
Use computational and machine learning methods on new or large datasets to identify insights with tools such as spreadsheets, databases, programming languages, and statistical or visualization software.
Conduct data quality reviews on court-wide caseload data from the enterprise data warehouse and major case processing systems.
Advise and consult with directors, managers, data points of contact, or address discrepancies to reach resolution; draft performance analysis and reports.
Develop and maintain data pipelines, scripts, documentation, and analytical methods to support long-term usability, transparency, and knowledge sharing.
Provide scientific, statistical, and technical consultation on applying best practices and new techniques.
Support enterprise data governance through proper data handling, documentation, access controls, and participation in development processes that enable secure and efficient data use.
Develop and execute business intelligence analysis and reporting for the Courts.
Collaborate with IT and other Court divisions to maintain data integrity across the Courts.
Code using languages such as Python or R; use SQL and other data processing and analytics tools to analyze datasets.
Use visualization tools such as MS Power BI, Tableau, MS Excel, and others to produce reports and communicate technical or statistical findings to non-technical audiences.

Requirements

Background and security investigation required.
One (1) year probationary period must be successfully completed.
Bachelor’s degree from an accredited university or college.
At least five (5) years collecting and analyzing data using databases and PC software to prepare statistical reports.
Upload a copy of your college transcript or degree for consideration.
Education must be accredited by an accrediting institution recognized by the U.S. Department of Education.
If using foreign education, submit a Certificate of Foreign Equivalency with your transcript at application time to receive credit.

Technologies

Python, R
SQL
MS Power BI, Tableau
MS Excel, spreadsheets
Databases
Statistical software, visualization software
Enterprise data warehouse

Benefits

Life Insurance
Retirement Benefits
Health Insurance
Workers Compensation
Supplemental vision and dental plans
Commuter transit benefit subsidy (maximum of $150/month)
Annual Leave
Sick Leave
Federal health plans (in addition to supplemental vision and dental plans)

Eligibility

Open to the public.
U.S. Citizens, Nationals, or individuals who owe allegiance to the U.S.
Clarification: United States Citizens or individuals lawfully admitted for permanent residency or authorized by USCIS to work in the United States.

Job Overview

Location: Washington, DC (onsite)
Work site options: Telework eligible (Yes, determined by agency policy)
Remote job: No
Relocation expenses reimbursed: No
Salary: $117,962 - $153,354 per year
Pay scale & grade: JS 13
Promotion potential: 13
Work schedule: Full-time
Travel required: 25% or less (you may be expected to travel)
Appointment type: Permanent
Occupations and job series: 1560 Data Science Series
Supervisory status: No
Federal service type: Competitive Service
Represented by a union: No
Drug test: No
Security clearance: Not Required
Position sensitivity and risk: Noncritical-Sensitive (NCS)/Moderate Risk
Background check type: Suitability/Fitness
Financial disclosure required: No
Accepting applications
1 vacancy
This job is not a federal position.

Evaluation

Reviewed based on how well you meet the qualifications.
Application package review ensures basic qualification requirements are met.
Questionnaire answers must be supported by your resume.
Resume must reflect relevant experience and demonstrate minimum qualifications.

Required Documents

Resume
Completed Vacancy Questionnaire
Documentation/Proof of Education (e.g., copy of college transcript or degree)
Three (3) professional references

How to Apply

Complete all required questionnaires and assessments and submit all required documentation.
Submit the complete application package by 11:59 PM (ET) on the closing date of the announcement.
Use the Apply Online button and attach all required supporting documentation.
Submit the application before 11:59 PM (ET) on the closing date.
To update during the announcement period: log into your USAJOBS account, find your application record, and click Edit my application.
Application status help: https://www.usajobs.gov/Help/how-to/application/status/.

Agency Contact

DC Courts Human Resources
Email: jobs@dccsystem.gov
District of Columbia Courts, 500 Indiana Ave NW, Washington, DC 20001

Next Steps

Qualified candidates will be referred to the hiring manager for further consideration and possible interview.
All applicants will be notified of the final outcome.

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Today

Data Scientist

Guidehouse San Diego, CA

San Diego, CA

Today

$113k - $188k/yr Full time Analytics Artificial Intelligence Automation Developer

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Job Description

The role will focus on preparing and analyzing data, building and sustaining machine learning and analytical workflows, and communicating results through reports, dashboards, and visualizations. The position requires an active Secret security clearance and relevant experience in data science, analytics, or applied statistics.

Key Responsibilities

Perform data preparation, cleansing, transformation, and exploratory analysis.
Support the development of machine learning models and analytical workflows.
Create reports, dashboards, and visualizations to communicate findings.
Assist with testing, validation, and performance monitoring of analytical models.
Support development of predictive analytics and forecasting solutions.
Collaborate with project teams to address operational and business questions using data analysis.
Document methodologies, assumptions, and analytical outputs.

Required Qualifications

An ACTIVE and MAINTAINED “SECRET” Federal or DoD security clearance.
Bachelor's degree.
Three (3) or more years of experience in data science, data analytics, or applied statistics.

Preferred Skills

Experience with Databricks or Palantir Foundry.
Experience developing ETL processes or automation solutions.
Knowledge of logistics, maintenance, readiness, or supply chain operations.
Experience supporting government clients.
Familiarity with Microsoft Power Platform.
Experience using Python, R, or SQL.
Experience with data visualization tools such as Power BI, Tableau, or Qlik.
Understanding of machine learning and statistical methodologies.
Ability to work in Agile project environments.

Technologies

Databricks
Palantir Foundry
Microsoft Power Platform
Python
R
SQL
Power BI
Tableau
Qlik

Compensation

USD 113,000 - 188,000 per year.

Work Location and Logistics

Location: San Diego, CA (onsite)
Travel required: Up to 10%
Clearance required: Active Secret

Benefits

Medical, Rx, Dental & Vision Insurance
Personal and Family Sick Time & Company Paid Holidays
Position may be eligible for a discretionary variable incentive bonus
Parental Leave and Adoption Assistance
401(k) Retirement Plan
Basic Life & Supplemental Life
Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts
Short-Term & Long-Term Disability
Student Loan PayDown
Tuition Reimbursement, Personal Development & Learning Opportunities
Skills Development & Certifications
Employee Referral Program
Corporate Sponsored Events & Community Outreach
Emergency Back-Up Childcare Program
Mobility Stipend

Job Family

Data Science Consulting

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1d ago

Data Engineer

Mindex Rochester, NY

Rochester, NY

1d ago

$90k - $140k/yr Full time Amazon Web Services Analytics Application Security

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Job Description

Mindex is hiring a Data Engineer to design cloud-native pipelines and analytics solutions for SchoolTool’s interactive dashboards.

Responsibilities

Build, test, scale, and maintain cloud-native data pipelines, data models, and warehouse structures for SchoolTool dashboards and analytics
Develop analytics solutions using Python, Apache Spark, Snowflake, SQL, NoSQL, and BI tools such as Amazon QuickSight, Tableau, or Power BI
Deliver large-scale, complex data solutions from data discovery and cleaning through model selection, validation, and deployment
Work directly with customer stakeholders, aligning execution with their roadmap and vision
Act as a primary point of contact when needed for stakeholder communication
Independently deliver well-defined data solutions and contribute to technical design decisions
Build technical and non-technical connections within your team, across Mindex delivery teams, and with customer stakeholders
Apply AI-assisted engineering practices and the AI DLC across planning, design, development, testing, documentation, and troubleshooting
Use an AI-first mindset to improve productivity, accelerate problem-solving, enhance quality, automate routine tasks, and support innovation

Requirements

AS or BS degree in Computer Science, Software Engineering, Physical Science, Mathematics, or a related field (preferred) or an equivalent combination of education and experience
3-5 years of data engineering experience, including implementing a data pipeline for an enterprise application
Experience with OLTP and OLAP databases
Hands-on experience with serverless platforms such as AWS Lambda and/or AWS Glue
Experience with infrastructure as code using AWS CloudFormation and Terraform
Familiarity with DevOps tools such as AWS CodePipeline, Azure DevOps, or GitLab
Strong communication skills to explain complex information to team members and customer stakeholders
Strong analytical, critical-thinking, and problem-solving skills with a focus on exceptional customer service
Highly organized and accurate, with strong initiative and follow-through
Comfort working independently and collaboratively in a self-organizing team, asking questions when needed and giving and accepting feedback
Use AI to augment expertise and decision-making while maintaining ownership, accountability, and professional judgment for final outcomes
Identify opportunities to use AI to streamline workflows, reduce manual effort, improve efficiency, and increase business value
Stay aware of emerging AI capabilities, tools, and best practices and proactively apply them in the workplace
Use AI technologies ethically, securely, and in a compliant manner while protecting confidential customer and company information
AWS Certification (Associate or Foundational) or applicable industry certifications (plus)

Technologies

Python, Apache Spark, Snowflake, SQL, NoSQL
Amazon QuickSight, Tableau, Power BI
AWS Lambda, AWS Glue, AWS CloudFormation, Terraform
AWS CodePipeline, Azure DevOps, GitLab

Benefits

Flexible Time Off
Medical, Dental, and Vision Insurance
401(k) with Company Match
Company-Paid Life and Disability Insurance
Professional Development Opportunities

Location and Work Requirements

Rochester, NY (onsite)
Candidates within approximately 35 miles of Rochester, NY may be asked to work from the office more frequently based on business or team needs
Occasional in-person participation is required

Licenses & Certifications

AWS Certification (Associate or Foundational) or applicable industry certifications (plus)

Additional Information

Applicants must be authorized to work for any employer in the United States
Mindex is unable to sponsor employment visas at this time

Physical Requirements/Conditions

Prolonged periods sitting at a desk and working on a computer
No heavy lifting expected; exertion of up to 10 lbs

Salary: USD 90,000 - 140,000 per year

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2d ago

Data Engineer

GM Performance Power Units Concord, NC

Concord, NC

2d ago

Full time Python Amazon Athena Amazon Emr

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Job Description

GM Performance Power Units is seeking a Data Engineer to build and operate AWS-based data pipelines that support power unit test and performance activities. In this onsite role in Concord, NC, you will help make engineering data accessible and traceable, connecting test results to approved engine, build, and component identities for analysis and business use.

What you’ll do

Build and maintain ingestion pipelines for agreed dyno, test rig, instrumentation, and performance sources, using batch, file, or streaming patterns when the requirements call for them.
Preserve source files and key timestamps, units, calibration references, run identifiers, and acquisition context, then implement validation to surface missing or disputed context.
Create documented datasets and processing pipelines using Python and SQL, including duplicate prevention, late-data handling, checkpoints, and controlled replay.
Link test runs to approved engine, build, and serialized component identities, collaborating with system owners to resolve mismatches while keeping mappings traceable.
Prepare and publish agreed test and performance summaries from the AWS environment for use by the business and manufacturing data platform, supporting controlled data exchanges and the reference data needed to connect test results to engines, builds, and components.
Monitor data freshness, pipeline failures, processing performance, and cloud consumption, tuning storage, retention, and compute to meet engineering and cost requirements.
Use source control, peer review, automated checks, and controlled deployment, maintaining separate development and production configurations and protecting credentials.
Document pipelines, dependencies, and recovery procedures, train a nominated deputy, and contribute to an agreed support and incident response model.

Required experience

Practical experience building and supporting production data pipelines on AWS, including Amazon S3 and the supporting processing, orchestration, and monitoring services.
Strong Python and SQL skills, including work with large files, time-series data, and complex engineering datasets.
Understanding of incremental processing, idempotency, schema changes, data quality controls, and recovery from partial failures.
Experience with Git, code review, testing, and repeatable deployments, including infrastructure as code and CI/CD practices.
Knowledge of cloud access controls, service identities, encryption, and secure connectivity, partnering with infrastructure and security specialists.
Ability to diagnose failures, explain cost drivers, and document a service so another engineer can maintain it.
Ability to translate engineering requirements into clear data contracts and acceptance tests, with effective communication across technical and business colleagues.
Relevant qualification or equivalent practical experience, with evidence of delivered outcomes.

Technologies you may work with

AWS, Amazon S3
Python, SQL
Git
Infrastructure as code, CI/CD
Microsoft Fabric, Power BI, Power BI integration
Parquet, Delta Lake
Glue, Athena, EMR, Kinesis
Databricks

Benefits

Bonus scheme
Private healthcare
401(k) plan including company match
Employer-paid life insurance and disability coverage
32 days annual leave (including holidays)
Free financial advisor access
Employee Assistance Programs (EAP)
Subsidized on-site dining
On-site gym
Discounted GM vehicle purchase/lease program
Free on-site EV charging for personal GM vehicles

Preferred qualifications

Experience in automotive, motorsport, aerospace, manufacturing, or another test-intensive engineering environment.
Knowledge of dyno or rig data topics such as signal alignment, timestamp synchronization, calibration context, telemetry formats, and engineering metadata.
Experience with Parquet or Delta Lake, distributed processing, and AWS services such as Glue, Athena, EMR, Kinesis, or equivalent tools selected for the workload.
Experience with cross-cloud data exchange and Microsoft Fabric or Power BI integration, including linking test results to PLM, ERP, or lifing records.
Databricks on AWS where justified by processing needs, with Databricks experience beneficial rather than required.

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2d ago

Data Engineer

Robotics Technologies Columbia, MO

Columbia, MO

2d ago

Full time Analytics Automation Developer Azure

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Job Description

This role focuses on building scalable data pipelines and analytics deliverables using Azure and related tools.

Responsibilities

Design and build data pipelines using Azure Data Factory, Databricks, and other cloud-native components
Develop ETL workflows for reliable ingestion, transformation, and storage of data
Partner with business stakeholders to translate reporting needs into actionable insights
Create and maintain Power BI dashboards to support decision-making across teams
Improve data workflow performance, scalability, and reliability
Maintain data quality and follow data governance standards across systems
Troubleshoot and resolve issues involving data pipelines, integrations, and reporting

Requirements

Hands-on experience with Microsoft Azure, including Data Factory, Synapse, and Storage
Proficiency in Databricks for big data processing and analytics
Python skills for data manipulation, automation, and integration
Expertise in Power BI for dashboard creation and data visualization
Strong foundation in SQL and relational database concepts
Experience with data modeling and performance tuning
Excellent communication skills to collaborate with both technical and non-technical stakeholders

Tech Stack

Azure Data Factory
Databricks
Python
SQL
Power BI
Microsoft Azure
Synapse
Storage

Location: Columbia, MO (onsite)

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2d ago

Senior Cloud Data Engineer

Rosen's Diversified, Inc. Green Bay, WI

Green Bay, WI

2d ago

Full time Analytics Artificial Intelligence Automation Developer

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Job Description

Build and optimize secure, high-performing cloud data solutions on Azure for manufacturing analytics and digital transformation.

Design, develop, and maintain scalable ETL/ELT pipelines using Azure Databricks, PySpark, Python, and SQL
Build and optimize ingestion frameworks for ERP, MES, Industrial IoT, quality, supply chain, inventory, finance, and related operational systems
Create reusable engineering patterns and standards to improve delivery speed, supportability, and reliability
Implement lakehouse solutions using Delta Lake and Medallion Architecture across Bronze, Silver, and Gold layers
Design and optimize data models for reporting, analytics, AI, and machine learning use cases
Maintain data lineage and documentation, including metadata, technical documentation, and operational runbooks
Integrate Azure Databricks with Azure Data Factory, Azure Data Lake Storage Gen2, Azure Key Vault, Microsoft Fabric, Power BI, and Azure DevOps
Support orchestration and data movement between enterprise applications and cloud platforms
Monitor and optimize Databricks clusters, jobs, notebooks, and workflows for performance, scalability, and cost efficiency
Troubleshoot production issues, identify root causes, and implement sustainable corrective actions
Contribute to operations, including monitoring, alerting, testing, and operational support practices
Apply standards for data quality, governance, privacy, security, and compliance
Implement governed data access with role-based access controls using Unity Catalog and Azure security services
Build automated controls for validation, auditing, and data quality within engineering workflows
Collaborate with stakeholders including business users, analysts, architects, and IT teams to translate requirements into maintainable solutions
Participate in Agile delivery with sprint planning, code reviews, and technical design reviews
Mentor junior engineers and promote best practices for coding, testing, documentation, and deployment

Requirements

Bachelor’s degree in computer science, information systems, data engineering, or related field; equivalent education and experience may be considered
3–5 years of experience in data engineering, cloud engineering, or analytics platform development
Minimum 2 years hands-on experience developing solutions with Azure Databricks
Experience supporting enterprise data solutions in a manufacturing or industrial environment
Strong knowledge of Azure Databricks, Apache Spark, PySpark, Python, SQL, Delta Lake, lakehouse architecture, data modeling, and data warehousing concepts
Experience with Azure Data Lake Storage Gen2, Azure Data Factory, Azure DevOps, Git source control, and CI/CD practices
Experience with data quality, security, monitoring, troubleshooting, and performance tuning
Knowledge of manufacturing data domains including ERP, MES, production planning, inventory, supply chain, quality management, maintenance, or Industrial IoT
Ability to work with operational stakeholders and translate manufacturing processes into reliable data requirements and solutions

Technologies

Azure Databricks
PySpark, Python, SQL
Delta Lake, Medallion Architecture
Azure Data Factory
Azure Data Lake Storage Gen2
Azure Key Vault
Microsoft Fabric
Power BI
Azure DevOps
Unity Catalog
Terraform, Bicep, ARM templates
Git, CI/CD

Benefits

Excellent health and welfare benefits including medical, dental, vision, disability, and voluntary benefit options
401(k) with annual company match for eligible employees
Professional and personal development programs, including Career and Learning Paths

Additional qualifications, knowledge, skills, and experience

Experience with Microsoft Fabric, Power BI, or real-time and streaming data workloads
Hands-on experience with Unity Catalog and governed lakehouse implementations
Exposure to machine learning or AI data preparation and deployment patterns
Experience with Infrastructure as Code using Terraform, Bicep, or ARM templates
Preferred knowledge of Infor M3, including application design, business data model, and core table structures used across manufacturing, supply chain, inventory, finance, and related functional areas
Preferred understanding of production, planning, inventory, quality, maintenance, and supply chain processes
Microsoft Certified: Azure Data Engineer Associate
Databricks Certified Data Engineer Associate or Professional
Microsoft Certified: Fabric Analytics Engineer Associate

Location: Green Bay, WI (onsite). Minimum experience: 3 years. Education: Bachelor’s degree in computer science, information systems, data engineering, or a related field.