Top Data Engineer Jobs

Design and build data infrastructure, pipelines, and integration solutions using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality and security, apply data modeling and DAGs, use Databricks, Airflow, and Hadoop, and collaborate with clients to deliver actionable insights.

Build and own the companys modern data platform: ingestion, orchestration, Snowflake architecture, dbt transformations and CI/CD, observability, governance, and a semantic layer to enable trusted analytics and production AI/ML workloads. Partner cross-functionally and automate recurring operational pain points into reusable platform capabilities.

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 data architecture, manage production data pipelines, lead projects, and ensure quality and documentation while supporting progressive politics through data-driven solutions.

The Staff Data Engineer will design and build data pipelines, reports, and tooling for the Concepts Lab, ensuring reliable AI systems and leading data modeling and analytics efforts. The role requires extensive experience in production data systems and collaboration across teams to transition concepts into production.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

Design, build, and maintain enterprise ETL/ELT pipelines and data management workflows for market, reference, and financial data in the Markit EDM platform. Implement ingestion, validation, reconciliation, enrichment, monitoring, and distribution processes; support reporting and downstream integrations. Troubleshoot production data issues, collaborate with stakeholders in agile squads, and mentor junior engineers to promote best practices.

Design, build, and maintain data connections and transformations to normalize external portfolio data into a standard Clearwater format. Automate monitoring, improve auto-reconciliation, implement solutions from data feeds, support projects and migrations, mentor hires, and communicate technical details to non-technical stakeholders.

Lead design, development, and implementation of data product features and reusable frameworks. Collaborate with architecture and stakeholders, drive technical decisions, deliver product implementations, and troubleshoot production issues. Emphasizes RESTful APIs and cloud/container technologies.

Lead design, build, and optimization of large-scale real-time and batch data ingestion and transformation pipelines. Integrate enterprise systems (SFDC, NetSuite, Workday), ensure data quality, observability, and reliability, and enable analytics/AI workflows. Architect solutions using Airflow, dbt, Python, Kafka, Snowflake, apply DevOps/CI-CD practices, mentor global teams, manage multiple projects, and align data engineering initiatives with product and business stakeholders.

Design, build, and maintain cloud-based data pipelines, lakes, lakehouses and warehouses for batch and real-time processing. Optimize SQL and data models, provide production support, and deliver BI applications while following Agile practices.

Lead operational design and engineering for the data platform: own Snowflake and dbt administration, automate platform operations and CI/CD, monitor platform health and observability, enforce governance and access, optimize performance and costs, and develop AI/agent integrations to enable governed data access for business users.

The Senior Data Platform Engineer will design, maintain, and enhance Hinge's data platform, including data pipelines, monitoring systems, and user feedback incorporation while ensuring data quality and system reliability.

As a Lead Data Engineer, you will design and implement data solutions using big data technologies, collaborate with Agile teams, and mentor other engineers.

The Lead Data Engineer will design, develop, and support complex technical solutions using Java, Python, AWS, and big data technologies. Responsibilities include collaborating with Agile teams, mentoring, and delivering cloud-based solutions.

The job involves leading a team to develop data-driven solutions, utilizing various programming languages and cloud technologies, while collaborating with Agile teams and mentoring junior members.

The Senior Data Engineer will build and optimize data pipelines, ensure data integrity, and collaborate with stakeholders to meet business requirements while implementing best coding practices.

The Data Architect will design and optimize data warehouses, analyze business intelligence data, and lead integration efforts to ensure solutions meet quality standards.

The Data Engineer will design data models, build data warehouses and lakes, automate data pipelines, and enable data accessibility while maintaining security standards in a complex environment.

Lead technical strategy and architectural evolution in marketing technology, mentoring teams and driving innovative solutions across data engineering and platforms.

Lead architecture and buildout of a new graph-backed enterprise data platform: design ingestion, graph and relational storage, entity resolution pipelines, temporal models, ETL/ELT pipelines, governance, APIs, and production connectors. Ship scalable graph data models, traversal queries, and platform roadmap while enabling observability, security, and containerized deployments.

Lead strategy, architecture, and delivery of enterprise data engineering on the Data Cloud Platform. Design batch and real-time pipelines, event-driven streaming, data products, governance, lineage, quality, and observability. Provide technical leadership, mentor teams, drive adoption of standardized data models, CI/CD, and align platform capabilities with business and investment use cases.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.

As a Senior Data Engineer, you will implement data ingestion patterns, build pipelines in Azure, and enhance development with AI tools, aiding the migration to a cloud-based architecture.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.