Top Data Engineer Jobs

Provide data architecture leadership for Payments Operations: define metadata, systems of record, data quality, and domain models; design data delivery and analytics capabilities; profile and transform data using Python/PySpark/SQL; collaborate with product, analytics, and tech teams; research emerging technologies and implement data solutions.

Design, implement, and manage advanced data ecosystems and scalable ETL/ELT pipelines. Analyze complex problems, deliver data warehousing and governance solutions, mentor junior staff, and build client relationships while maintaining high standards and business-context awareness.

Lead design and implementation of data architecture, ETL/ELT pipelines, data models, warehouses and lakes. Ensure data governance, security, cloud deployments, performance and cost optimization. Coach and manage team members, partner with stakeholders, and drive data-driven solutions for clients.

Lead design and implementation of enterprise data architecture and cloud-based data solutions. Manage large data engineering projects, develop data models and pipelines, ensure governance and security compliance, advise clients strategically, and build high-performing inclusive teams.

Design and implement data architecture and scalable ETL/ELT pipelines on cloud platforms (AWS/Azure/GCP). Analyze complex problems, mentor junior staff, ensure data governance/security compliance, liaise with stakeholders, and deliver high-quality client solutions while developing technical and client-facing skills.

Design and build data infrastructure and pipelines using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality and security, collaborate with clients, and apply data architecture, transformation, and analytics to deliver insights.

Develop and maintain data pipelines and ETL processes, optimize SQL and data architectures, build BI reports and dashboards (Oracle BI, QlikView, Spotfire), analyze data to produce strategic insights, support client engagements in regulated environments, and apply continuous process improvements to ensure data quality and integrity.

The Data Engineer II will build and optimize data pipelines, develop reusable data sets, and ensure data integrity and security.

Designs, builds, and maintains moderately complex cloud-based data systems, streaming and batch pipelines, and data infrastructure. Partners with stakeholders to implement scalable data formats, models, deployment pipelines, and prototypes to support analytics and reporting.

The Data Engineer will build and maintain data pipelines, optimize workflows, manage infrastructure, and enhance pipeline observability while collaborating with teams for effective data delivery.

Develop and maintain data pipelines and BI solutions for smart factory initiatives. Design data models, document data warehouses, build KPI dashboards, support ad-hoc analysis, and collaborate with stakeholders to enable data-driven decisions.

Design and operate scalable data systems for People Analytics, ensuring reliability and privacy of sensitive employee data. Collaborate with leadership to create data products for decision-making.

Design and implement ETL pipelines, optimize data systems, build data warehouses, and develop AI/ML models for data solutions. Collaborate with teams to deliver data-driven products and ensure data quality and governance.

Design, build, and maintain ELT/ETL pipelines into Snowflake using SQL, Python, Dataiku, and Databricks. Enable Tableau analytics, ensure data quality/governance, automate workflows, perform performance tuning, and collaborate with Finance to translate business requirements into reusable finance data products.

Design and deliver end-to-end web applications and data pipelines that integrate enterprise systems (including Oracle). Build high-performance data models, dashboards (Power BI), REST APIs, and UI components. Integrate tools like Jira and Smartsheet, implement logging/instrumentation (ELK), and collaborate in Agile to provide documentation, training, and ongoing support.

Build and improve end-to-end simulation data workflows and automation for vehicle dynamics: generate, store, process, validate, and analyze simulation datasets; implement CI/CD pipelines, Databricks/SQL-based data management, and automation; partner with simulation engineers to standardize metadata, drive reuse, and train teams toward data-driven simulation practices.

Design, build, and operate big-data and streaming platforms (Kafka, Hadoop, Dremio). Develop, deploy, and monitor data pipelines using Java, Python, Spark/Flink; collaborate on data modeling and ingestion, ensure data integrity and availability, act as a Big Data SME, and perform root-cause analysis.

The Data Engineer will develop and implement ETL processes, design data architectures, work with data platforms, and ensure data solutions meet scalability and security needs. Responsibilities include mentoring junior engineers and collaborating with stakeholders to gather requirements and optimize data transformations.

Design and build data models, warehouses and lakes; automate ETL pipelines; integrate and troubleshoot diverse data streams (structured and unstructured); analyze logs and complex networks; develop standards, governance, and analytic tools to enable secure data access and downstream consumption.

Design, develop, and maintain end-to-end data pipelines and data products for analytics. Troubleshoot complex data issues, document data sources, onboard backend and 3rd-party data, mentor peers, evaluate and deploy new tools, and collaborate with business partners to enable data-driven decisions.

Lead design, development, and operation of large-scale Spark-based data pipelines and lakehouse solutions. Write and review Python/PySpark and Spark SQL production code, optimize Spark workloads on EMR/Databricks, manage Apache Iceberg table operations, drive AI-assisted engineering adoption, automate reliability and CI/CD practices, and lead technical evaluations and communities of practice.

Design, build, test, and maintain secure, scalable data collection, storage, access, and analytics solutions. Develop and maintain ETL pipelines and data architectures, update logical/physical data models, review data controls, perform statistical data analysis, customize tooling to generate products, and work with SQL and NoSQL databases.

Build, model, and maintain scalable BigQuery-based data solutions on GCP. Implement performant data models, storage partitioning/clustering, ETL improvements, data validation, and documentation. Collaborate with architects, data scientists, and engineers to deliver governed, high-quality data for reporting and AI initiatives.

Design, build, and maintain scalable Snowflake-based data platforms and ETL/ELT pipelines; operationalize AI/ML models; automate processes; monitor and optimize code and data systems; support data governance and engage cross-functionally to deliver analytics and predictive solutions.

Design, build, and maintain scalable ETL/ELT pipelines and data warehouse architecture. Partner with cross-functional teams to define KPIs, ensure data quality and governance, own billing data infrastructure, and deliver dashboards and analytics for leadership while mentoring peers.