Top Data & Analytics Jobs

Lead complex data, analytics, AI, and cloud transformation engagements as a trusted advisor: manage delivery, scope, budget, stakeholders, and teams; design scalable data platform solutions; drive business development, mentoring, and practice improvements.

Own end-to-end data pipelines (ingest, dbt transformations, BigQuery warehousing) and consolidate the analytics stack into a single source of truth. Build and maintain dbt models with tests and documentation, establish data quality and observability, own product analytics and instrumentation, partner with GTM and marketing on reporting, and prepare for high-volume/streaming ingestion.

Lead architecture and technical strategy for enterprise-scale cloud data platforms. Design scalable ETL/ELT pipelines and data models, drive governance, implement AI-assisted engineering tools, mentor senior engineers, and ensure secure, performant, and maintainable data solutions.

Design, build, and maintain ETL/ELT data pipelines and databases; implement data quality checks; support analysts and data scientists; integrate ML models; automate workflows; document processes and train stakeholders.

Support extraction, querying, and analysis of DMLSS/LogiCole logistics and supply chain data. Build data models, automate ETL with Excel/Power Query, reconcile financial/logistics data for AFWCF audit, respond to auditors, merge/clean disparate DoD datasets, and design scalable dashboards and reports for leadership.

Build and maintain Power BI/Qlik dashboards and integrated CRM/ERP data models, monitor CRM data quality, analyze pipeline/forecast/revenue/margin, and deliver KPI-driven insights, documentation, training, and ad hoc analysis to Sales and RevOps leadership.

Lead and scale the data engineering function for P&C insurance domains. Own enterprise data architecture, ETL/ELT pipelines, Snowflake-based warehousing, data governance, data quality, and cross-functional delivery while managing and mentoring teams to align data initiatives with business strategy and compliance.

Design, build, test, and maintain scalable cloud-based data platforms and ETL/ELT pipelines (batch and near-real-time). Implement data models, data marts, governance, metadata, CI/CD and IaC, optimize pipeline performance, support migrations/DR, produce documentation, and collaborate with architects, DBAs, and stakeholders to meet federal security and audit requirements.

Design, build, and manage a scalable enterprise music data platform and pipelines. Collaborate with product and business teams, maintain data governance, perform data modeling, monitoring, testing, and troubleshooting, and mentor teammates. Ensure compliance with standards and support analytics, reporting, and integrations across multiple sources and targets.

The Data Engineer will build and maintain scalable data pipelines, improve ETL processes, collaborate with AI/ML teams, and contribute to engineering culture.