Top Data & Analytics Jobs

Build and maintain production data pipelines and foundations for People Analytics and AI-driven tools. Integrate HR systems (Workday, Greenhouse), design data models, ensure governance for sensitive employee data, support data science and reporting, and deliver dashboards and Streamlit apps. Optimize queries, enable LLM consumption with quality and latency controls, and collaborate cross-functionally to transition AI prototypes to production.

Design, build, and maintain dbt data models and scalable ELT pipelines; optimize performance-aware SQL on Snowflake; ensure observability, testing, and CI/CD; partner with product and engineering teams to meet analytic needs, mentor engineers, document business logic, and troubleshoot ingestion, transformation, and warehouse issues.

Lead design, development, and governance of enterprise ontologies, semantic layers, and knowledge/ entity graphs. Implement graph and vector databases, enable LLM-augmented search and federated data access across Snowflake, Databricks, PostgreSQL, MongoDB, S3, and Kafka. Drive data cataloging, security models, ontology governance, and mentor teams to translate business goals into ontological solutions.

Lead enterprise data governance for Disney's Data Unification initiative: define and enforce policies, embed governance in semantic models and federated platforms, ensure security/privacy/compliance, implement metadata/lineage/quality strategies, support semantic data products and AI governance, and drive adoption and reporting.

Build and maintain reliable, observable data pipelines and a dbt-based transformation layer. Create analytics data models for in-product client reporting and internal dashboards, enforce data quality checks, and collaborate with Product and commercial teams to support analytics needs.

Design, build, and operate a scalable, secure data platform. Architect end-to-end data pipelines, manage Snowflake performance and costs, implement CI/CD and observability, ensure data governance and HIPAA alignment, integrate diverse sources, mentor teammates, and support analytics and business users.

Design, build, and operate scalable data platform services and ETL/ELT pipelines that transform billions of events into trusted, low-latency data products. Own data quality, observability, SLAs, incident response, and platform tooling, drive architectural decisions, and mentor engineers to enable self-serve analytics and product capabilities across the organization.

Lead design and build of data ingestion, ETL/ELT pipelines, and data models across HANA, Azure and Snowflake. Create reusable frameworks, SQL transformations, data quality and ABCR models, and automation for pipeline testing and code migrations while collaborating with architects, product owners and business teams.

The Staff Data Platform Engineer will develop integrations and data pipelines across multiple enterprise systems, ensure data quality, and support executive analytics and AI capabilities.

Responsible for IT strategy and solutions in R&D, overseeing system integration, stakeholder collaboration, and project prioritization at Zoetis.

The Senior Data Engineer will construct and optimize data pipelines, work with cross-functional teams, ensure data quality and governance, and mentor junior engineers while leading advanced analytics initiatives.

As a Data/Analytics Engineer, you will lead data architecture projects, ensure data quality, implement analytics algorithms, and integrate third-party data systems.

The Data Engineer will lead data modeling efforts for Navy and DoD projects, integrating engineering methodologies, overseeing data solutions, ensuring quality and alignment with project goals, and collaborating with cross-functional teams.

Design, build, operate, and optimize large-scale data pipelines and foundational data products for Komodo's Healthcare Map. Improve pipeline reliability, observability, and performance; transform claims and EHR datasets; implement data quality, lineage, and monitoring; debug production workflows; collaborate with product and engineering teams; and enable downstream analytics and AI/ML use cases.

Design, build, and implement mission dataflows and data pipelines. Develop end-to-end software solutions (front-end, back-end, APIs, infrastructure) from prototype to production, collaborate cross-functionally, identify system improvements, and support future enhancements in an agile environment.

Design, build, and maintain scalable data pipelines and platform tools; define canonical data models; deploy and operate workflow managers (Airflow/Jenkins); work with cloud data tools (Redshift, EMR) and infra (Kubernetes, Terraform); implement data security controls; mentor junior engineers and collaborate with data scientists, analysts, and product teams.

Design and own a multi-tenant data transformation platform: tenant onboarding, schema/ontology evolution, correctness guarantees, RBAC/isolation, agentic and API access, real-time sync, orchestration migration, and governance to scale data products for AI-driven marketing.

Design, build, and scale data-driven solutions and high-volume ETL/ELT pipelines for equity research. Develop cloud-based (AWS) data architectures, ensure data modeling, governance, performance tuning, and collaborate with data scientists and business partners in Agile environments.

Design, build, and maintain scalable ETL/ELT pipelines and data models to populate the data warehouse. Write reusable SQL and Python to transform data, monitor pipeline reliability and quality, enable AI workflows, collaborate with stakeholders, and drive adoption of modern data stack technologies (DBT, Iceberg, Databricks). Support data governance, observability, and security practices.

Design, build, and maintain scalable ETL/data pipelines and analytics solutions. Create data models, ensure data quality and governance, implement CI/CD and version control for data workflows, and develop Tableau dashboards to deliver insights for stakeholders.

Design and maintain data pipelines (SQL, dbt, BigQuery), ensure data quality and event tracking, analyze A/B tests, build funnel and attribution reporting, create Looker dashboards, and support LLM-enriched data models for smarter targeting and segmentation.

Technical lead on the Distribution Center data team building and scaling ETLs and data integrations using PySpark and DBT. Design robust pipelines to process large customer datasets, improve onboarding tooling, mentor engineers, manage contractors, and collaborate cross-functionally to support ML-driven grocery solutions.

Senior Data Engineer with 10+ years and mandatory Azure certification. Hands-on with MS Fabric, T-SQL, ETL/ELT, data modeling, cloud platforms (Azure/AWS/GCP), and data orchestration. Must work independently, possibly lead junior team members, communicate clearly, and be available for onsite-hybrid work in Lansing, MI. Long-term contract.

Lead design, build, and optimize Azure-based data pipelines and Databricks ETL workloads. Integrate diverse data sources, enforce data governance and quality, implement medallion architectures, tune performance, support analytics/ML use cases, and mentor stakeholders and team members.

Design, build, and operate scalable end-to-end data pipelines and curated data products to support enterprise analytics and agentic AI. Integrate structured and unstructured data, provide APIs and retrieval/indexing for AI agents, implement data quality, observability, governance, optimize cost/performance, and collaborate with cross-functional teams to deploy production data solutions.