Top Data & Analytics Jobs

The Business Intelligence/Data Cube Developer will generate reports and data cubes, write custom ETL jobs, and support analytics for a federal agency.

The Senior Data Engineer will manage data tuning on relational databases, utilize Big Data technologies, and coordinate with technical teams and business users.

Lead design and implementation of the enterprise data platform: architect scalable warehouse/lakehouse solutions, build and optimize ETL/ELT pipelines, enforce data quality and governance, tune analytical workloads, and enable reporting and self-service analytics in support of BI and AI initiatives.

Lead the analytics data layer: design and operate a ClickHouse-backed warehouse, define and validate trusted metrics, build customer-facing React dashboards and internal Grafana/self-serve tooling, and ensure data quality, lineage, and documentation for telemetry-derived insights.

The Staff Data Engineer will build and optimize data pipelines, ensure data reliability, collaborate with teams, and shape the data engineering landscape at CookUnity.

Lead and architect large-scale data products and pipelines across teams. Design and deliver ELT/ETL solutions, evaluate tools, ensure scalability and integrity, influence technology decisions, and research emerging big-data/cloud methodologies (AWS, Hadoop/EMR, Spark, Kafka, Snowflake). Partner with architects and stakeholders to drive implementation and operationalize production workloads.

As a Senior Data Engineer, you will build complex data solutions and pipelines, support analytics growth, and educate users. Collaboration and advanced technical skills are essential.

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, build, and maintain cloud-based data pipelines and ETL processes to populate data warehouses. Optimize storage and performance, enforce security and data quality, automate tasks with scripting, mentor junior engineers, and evaluate new technologies to improve scalability and reliability.

Design, build, and maintain cloud-based data pipelines and ETL into data warehouses (Snowflake/AWS). Ensure data quality, security, and performance; optimize storage and retrieval; automate tasks with Python/Bash; monitor/troubleshoot pipelines; mentor junior engineers; evaluate new technologies and support legacy systems.

Own and improve the company data stack: expand the data warehouse, build and streamline Python-based ingestion and ETL processes, refactor dbt models, maintain data quality, standardize reporting, and collaborate with engineering and analysts. Act as technical owner for parts of the stack and proactively drive improvements and automation.