Top Data Engineer Jobs

Design, build, and maintain scalable Azure data pipelines and platforms using Azure Databricks, Synapse, Fabric, and Data Factory. Implement IaC (Bicep/ARM/Terraform), CI/CD with Azure DevOps, optimize Spark jobs, monitor platform stability, and collaborate with architects, BI developers, and clients to meet Azure best practices and business requirements.

Design, build, and optimize GCP-based data architectures and ETL/ELT pipelines using BigQuery, Dataflow, dbt, and orchestration tools. Ensure data quality, security, and integration from diverse sources; collaborate with stakeholders to deliver actionable insights.

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.

Lead technical strategy and roadmap for an enterprise Databricks-based data platform. Drive governance, metadata, lineage, and semantic layer standards; build reusable data products; enable self-service analytics and scalable ML operations; mentor engineers and align platform investments with business outcomes.

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.

Lead Data Engineer builds and maintains foundational, cloud-based data platforms for transaction analytics. Collaborates with Agile teams to design, develop, test, and deploy data solutions using big data, streaming, and warehousing technologies, mentors engineers, and ensures performant, production-ready code.

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

The Senior Principal Data Analytics Engineer will lead transformations in data architecture and analytics, focusing on high-quality, accessible data for decision-making, while collaborating with teams, ensuring governance, and optimizing performance.

The Senior Lead Data Engineer will design, develop, and support technical solutions, lead a team, and work with cloud-based services, focusing on data integration and transformation.

As a Lead Data Engineer, you'll design and build scalable data platforms, develop streaming data pipelines, and collaborate within Agile teams to implement data solutions.

As a Lead Data Engineer, you'll lead the design and implementation of scalable data platforms, build distributed streaming data pipelines, and collaborate on technical solutions using big data technologies and agile methodologies.

Design, build, and maintain ETL pipelines and serverless AWS workflows for asset and cash-flow data; develop AI proof-of-concepts; integrate data sources and APIs; ensure security, monitoring, and production support; collaborate cross-functionally and maintain documentation.

Lead design and delivery of complex, scalable data solutions and pipelines using SQL, Python, Synapse, Snowflake, dbt, and Fivetran. Ensure data quality, security, observability, and compliance (GDPR/HIPAA), mentor engineers, conduct architecture reviews, drive automation and cost/performance optimization, and partner with cross-functional teams to implement governance and data lineage.

Design, build, and maintain scalable GCP data pipelines and ETL/reverse ETL processes using Dataflow, Dataform, and BigQuery. Develop secure APIs for ingestion, optimize data models and Datastream integrations, implement monitoring, and ensure GDPR/CCPA-compliant data governance for player analytics and fraud detection.

As the first Data Engineer, design and implement a scalable data platform, build data pipelines, and establish data modeling standards. Enable BI accessibility and document core metrics.

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

Design and optimize data pipelines for web scraping and processing data. Collaborate with ML engineers and develop APIs while preparing data for analysis.

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.

As a Growth Data Engineer, you will build and manage marketing data and attribution systems, ensuring reliable data flow and accurate measurement of acquisition efforts. The role involves collaboration across product, marketing, and data teams with a focus on optimizing campaign performance.

The Founding Data Engineer will design and build OpenArt's core data platform, ensuring data reliability, consistency, and scalability to support leadership and product metrics.

The Lead Data Engineer will develop and optimize data pipelines, mentor the engineering team, and ensure data integrity and compliance while collaborating on business insights.

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, implement, and manage cloud-based databases and data delivery systems. Configure and ingest structured, semi-structured, and unstructured data. Perform streaming and batch processing, ETL, data wrangling, and data access. Advise on cloud migration, recommend tools, and guide teams to meet standards and solve complex enterprise network operations challenges.

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.

Design, build, and scale resilient data pipelines and infrastructure on AWS. Own the data ecosystem using Databricks or Snowflake, write production-quality Python and SQL code, collaborate with cross-functional teams, and prepare data for analysis and product use in a fast-moving startup environment.