Top Data Engineer Jobs

As a Data Engineer, you will design and build robust data pipelines, manage data infrastructure, and support data-driven strategies using advanced engineering techniques.

Support development and maintenance of data pipelines, ETL processes, and data integrations. Assist with data infrastructure (databases, warehouses, lakes), implement data validation and quality checks, participate in code reviews, document processes, and collaborate with engineers and analysts while learning and following established standards.

The role involves architecting intelligence infrastructure, building data pipelines, collaborating with other teams, and ensuring data accessibility and security for threat detection systems.

Own and operate the unified data platform and data lake powering fraud detection. Design, build, and run low-latency batch and streaming ingestion pipelines, ensure data quality/lineage/observability, support embedding/vector pipelines for generative AI, and manage deployment and CI/CD on Kubernetes while partnering with data science and product teams.

The Sr. Data Engineer is responsible for application development, database performance monitoring, data analytics, and ensuring compliance with quality standards.

The Data Engineer will build data transformation systems and connect diverse data sources to create transparent pricing for small businesses. Emphasis on accuracy and customer satisfaction is key.

The Data Engineer IV is responsible for designing and building data pipelines, implementing transformation logic, ensuring data quality, optimizing data infrastructure, and collaborating with stakeholders. This role requires advanced skills in data engineering, management of projects, and mentoring of junior developers.

Lead design, build, and maintain scalable data pipelines, warehouses, and analytics environments. Integrate diverse data sources, ensure data quality and security, define SLAs, perform ad-hoc data analysis, and collaborate with product and project teams to deliver BI and analytics solutions.

Technical owner of the Microsoft Fabric and OneLake data platform: design medallion architecture, manage ingestion and transformations, enforce CI/CD and engineering standards, ensure monitoring/performance/cost optimization, implement data quality/lineage/security, enable GenAI via Azure AI and Foundry (RAG), and lead/vendor/manage engineering hires and outsourced partners.

The Data Engineer will design and maintain data pipelines, optimize cloud data warehouses, and collaborate with analytics teams while mentoring junior staff.

Design, implement, and maintain scalable data pipelines and platforms for structured and unstructured data to support AI/ML workloads. Ensure data governance, security, monitoring, and CI/CD for ETL workflows across on‑prem, cloud, or hybrid environments while collaborating with cross‑functional technical teams.

Design, develop, and monitor large-scale cloud-native data solutions and ETL pipelines; support ML model deployment, ensure code hygiene and CI/CD, mentor engineers, produce documentation and runbooks, and engage with clients to deliver analytics-driven solutions.

Build and maintain data platform and production data warehouse; translate PM and quant requirements into technical solutions; design ETL, data modeling, cleansing, monitoring, and alerting systems; evaluate new tooling; optimize performance and manage vendor relationships.

The AWS Cloud Data Engineer will design, develop, and enhance AWS data environments, build scalable Data Lake solutions, and lead proofs-of-concepts into production.

Design, build, monitor, and optimize scalable ETL/data pipelines on Azure. Collaborate with scientists and engineers to integrate systems, support analytics/ML, and ensure performance, cost-effectiveness, and data governance.

Design, build, and maintain high-throughput data processing services, focusing on streaming and batch data systems to enhance player experiences.

Lead and mentor a data engineering team to design, build, test, and deploy cloud-based, AI-enhanced risk management data solutions. Collaborate across Agile teams and product managers, implement big-data and streaming systems, perform unit tests and code reviews, and drive technology adoption and performance tuning.

The Senior Data Engineer will design and maintain data pipelines, build reusable data sets, validate data integrity, and ensure user privacy and security. This role requires strong expertise in SQL and Python, and familiarity with AWS and various data technologies.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

The Data Engineer will design and build solutions for investment insights using big data technologies, developing data pipelines, and collaborating with cross-functional teams.

Design, develop, and maintain databases and scalable data pipelines. Build stored procedures, triggers, and ETL processes; perform testing, tuning, security, and data quality work. Collaborate with developers and stakeholders, document architecture, review code, and support reporting and integrations to enable restaurant and customer-facing systems.

Design, build, and maintain scalable data pipelines and stores; develop ETL/ELT workflows; process structured and unstructured data; collaborate with analysts and developers to deliver data platforms and solutions for mission-driven clients. Support deployments, analytics, and occasional travel; requires Secret clearance.

Build, operate, and monitor ETL/ELT pipelines between marketing, sales, and operational systems into Databricks. Implement dimensional models, identity resolution, data quality checks, API integrations, and scheduled/event-driven syncs to support segmentation, attribution, and campaign activation. Maintain documentation, alerting, and runbooks.

Designs, builds, and operationalizes complex Databricks/AWS data solutions and pipelines. Performs data analysis, cleansing, testing, and incident resolution while incorporating governance, security, and quality. Collaborates across teams, supports end users, and provides technical leadership to deliver production-ready data products for analytics, ML, and AI use cases.

Build and maintain ELT/ETL data pipelines and services using Python, SQL, and Spark. Work with Airflow, CI/CD, and AWS infrastructure; write well-tested code, participate in code reviews, and collaborate with product and data science teams to deliver data solutions for search, graph, and relational stores.