Top Data & Analytics Jobs

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, 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.

Design and implement scalable data architecture and storage (cloud/on-prem), build and maintain ETL pipelines, enforce data governance and security, ensure data quality, evaluate technologies, collaborate with analysts and data scientists, and document data assets.

Design, build, and maintain scalable batch and real-time data pipelines and platform components. Produce curated datasets, ensure data quality, observability, and lineage, and collaborate cross-functionally to deliver data products that support analytics, experimentation, and ML.

Build and maintain ingestion pipelines, Python services, and dbt models on AWS and Snowflake. Own operational on-call responsibilities, migrate pipelines to Airflow, contribute to CI/CD, collaborate with BI/Analytics, and mentor junior teammates.

Design, architect, and deliver scalable data pipelines and storage solutions using big data and cloud technologies. Lead technical strategy, mentor engineers, ensure data governance, security, and performance, and collaborate with Data Science and Product teams to support analytics and ML initiatives.

Lead end-to-end data engineering on GCP: design scalable data platforms and architectures (lake/lakehouse/warehouse), build and optimize BigQuery/Spark pipelines, ensure data quality/security, enable ML workflows with Data Science, mentor engineers, and own delivery and performance.

Design, build, and optimize data pipelines and storage solutions. Ensure data accuracy and performance, provide technical support, and collaborate with data scientists and stakeholders to resolve data issues and meet requirements.

Design, build, and optimize scalable AWS-based data pipelines, data lakes, and warehouses. Migrate legacy systems, enforce data quality/security/governance, implement ETL/ELT and big-data solutions, adopt CI/CD and IaC, collaborate with stakeholders, and provide technical leadership and troubleshooting.

Design, build, and maintain scalable ETL/ELT data pipelines and BigQuery data models. Implement Airflow workflows, CI/CD for deployments, ensure data quality and performance, and collaborate with data scientists, analysts, and business teams to deliver reliable analytics-ready data.

Lead architecture and delivery of a cloud-native, petabyte-scale data platform: define technical roadmap, mentor engineers, build ETL/ELT pipelines, enable real-time streaming, implement Iceberg table format, optimize Snowflake/Redshift/Athena compute, and integrate observability with Splunk.