Top Data & Analytics Jobs

The Data Engineer II will manage analytics pipelines for mobile games, transforming telemetry data and ensuring data quality for studio teams' decisions.

The Principal Data Engineer will manage the analytics data architecture, engage cross-functionally, and create reliable data systems using Snowflake and Python on AWS.

Build and maintain data ingestion and transformation pipelines on Microsoft Fabric/Azure, prepare analytics-ready datasets, write and optimize SQL, validate data quality, create Power BI reports, collaborate with stakeholders, support deployments, testing, documentation, and ongoing dashboard enhancements for Sales and Marketing.

Design, build, and maintain scalable analytics solutions on Microsoft Fabric and Azure. Gather requirements, model data, develop ETL pipelines with SQL and Python, support data lake and governance, provide technical leadership, and create reports using Power BI/Tableau.

Design, build, and maintain ETL/data pipelines and data warehouse solutions. Ensure data quality, perform data modeling, support analytics and data science, act as SQL Server DBA, integrate third-party systems/APIs, optimize platform performance, collaborate with stakeholders and vendors, and manage platform roadmap and reporting backlog while following IT policies and Agile/CI/CD practices.

As a Data Engineer, you will design and maintain data pipelines, ensure data quality, integrate systems, and support reporting tools for decision-making.

Design, build, and maintain scalable data lakes, warehouses, and production ETL/ELT pipelines. Automate data pipelines, ensure data quality via testing, collaborate with architects, data scientists, and DevOps, integrate data solutions into client environments, and implement data recovery and security measures.

Design, build, and maintain scalable batch and near-real-time data ingestion, transformation, and curation pipelines using Databricks and AWS. Support full pipeline lifecycle (intake, profiling, development, testing, release), implement data quality and observability, enforce metadata/lineage/governance, integrate with enterprise services, and prepare curated datasets for SQL and BI consumption.

Design, build, and operate scalable Databricks-based data ingestion and transformation pipelines on AWS. Ensure governed, observable, production-grade lakehouse solutions with metadata, lineage, data quality, security controls, and CI/CD deployment to support analytics and regulatory compliance.

Design, build, and maintain scalable ETL/ELT pipelines using Python and SQL. Implement CI/CD and DevOps practices for data workflows, automate ingestion, transformation, validation, and monitoring, and optimize production-grade data systems while collaborating with cross-functional teams.

Design, implement, and optimize large-scale data processing on Databricks and Spark. Build ETL pipelines, integrate data across AWS services (Redshift, RDS), orchestrate workflows with Airflow, and ensure data warehousing and engineering best practices. Lead and mentor development teams and collaborate with cross-functional stakeholders to drive data strategy and execution.

Lead design and hands-on delivery of a next-generation data platform and pipelines (batch, ELT, near-real-time) powering BI, experimentation, and ML. Own platform architecture, data modeling, governance, observability, and mentor engineers while modernizing legacy systems and driving AI-first data engineering practices across cross-functional teams.

Design, build, and maintain scalable ELT pipelines and data models for insurance (Guidewire) domains and Generative AI. Ensure data quality, performance, governance, and security; support analytics, AI model training (embeddings, vector DBs), dashboards, testing, and mentoring.

Lead design and implementation of Snowflake-centered cloud data platform and scalable ETL/ELT pipelines. Build data models, ensure governance/HIPAA compliance, optimize performance and costs, create Power BI reports, mentor engineers, migrate legacy systems, and enable analytics and AI/ML initiatives through robust data integration, testing, CI/CD, and security practices.

Builds and maintains ETL and database pipeline architectures, automates data collection and validation, supports data modeling and reporting, collaborates with stakeholders and data science to integrate models, coaches junior staff, and implements governance and technical solutions for large datasets.

Design, build, and optimize end-to-end data pipelines and architectures on cloud infrastructure (AWS). Implement ETL/dataflow artifacts, support stakeholders, provide Tier 3 support, automate processes for scalability, and collaborate on product vision and roadmaps while supporting off-hours deployments as needed.

Designs, builds, and maintains ingestion, transformation, and storage pipelines across Unclassified to Top Secret enclaves using Airflow, Spark, Glue, and Kafka. Implements data quality, encryption, access policies, documentation, monitoring, and provides Tier-2/3 incident support to ensure reliable data movement and analytics readiness.

Design and deliver cloud-based data architectures, ETL/ELT pipelines, and data lake/warehouse solutions for a Department of War client. Lead a small engineering team, implement migration strategy, build live-data dashboards, recommend tools, and coordinate with government PM. Hybrid role at Fort Bragg with quarterly travel; requires active Secret clearance and US citizenship.

Build and support high-performance data solutions, design and operate ETL pipelines and data warehouses, monitor production analytics tools, troubleshoot system issues, collaborate with product teams, and support TechOps for analytics infrastructure.

Design, build, and operate Azure-based data pipelines (batch and near real-time) using Databricks, PySpark, Delta Lake, dbt and Snowflake. Ensure data quality, SLA ownership, CI/CD integration, and leverage AI-assisted tools (Claude/Copilot) to optimize engineering workflows in a telecom environment.

Build and maintain cloud-native data pipelines and architectures (warehouse, lakehouse, streaming) to support BI, analytics, ML, and GenAI. Collaborate with data scientists and stakeholders to produce AI-ready datasets, enforce data quality and governance, optimize performance and cost, and implement ingestion, ELT, and observability practices under mentorship.

Build and maintain scalable ELT pipelines and analytics-ready datasets in SQL Server. Integrate SaaS/APIs, implement automated data validation and testing, develop star/snowflake data models, optimize performance, and support BI integration (Power BI) while partnering with stakeholders and documenting data systems.

Design, build, and maintain scalable data pipelines, storage, and analytics infrastructure for resource and project management. Collaborate with stakeholders to define requirements, optimize performance, document systems, and support deployments and cloud operations.

Design, implement, and maintain scalable ETL and real-time data pipelines using Apache NiFi; architect and optimize Snowflake data warehouses; administer Linux-based cloud environments (Azure/AWS/GCP); build CI/CD workflows; enforce data governance, lineage, and auditing; troubleshoot platform issues; mentor staff and document best practices to support micromobility and delivery analytics for the Department of Sustainable Delivery.

Design, deploy, and scale data infrastructure and automated open-source pipelines to produce high-quality public and geospatial datasets. Operate ingestion pipelines, transform and geocode spatial data, run QA/QC, design new data products end-to-end, modernize legacy systems, and collaborate on sprint planning, code review, and documentation across teams and agencies.