Top Data Engineer Jobs

Lead end-to-end analytics solutions: gather requirements with stakeholders, build production-quality ETL and visualizations, coach junior analysts, communicate progress and roadblocks, support proposals and pitches, and contribute to firm initiatives and client delivery.

Design, build, and optimize Snowflake-based data platforms and DBT models. Develop ingestion/replication pipelines, profile source data, ensure data quality, and support analytics and reporting through advanced SQL and collaboration with architects and stakeholders.

Design, build, and maintain scalable batch and streaming data pipelines and analytics-ready data models. Implement cloud (primarily AWS) data platform solutions, data ingestion, transformation, orchestration, and observability. Embed data quality, governance, security, and metadata/lineage practices. Partner with architecture, analytics, and application teams to enable self-service analytics, reporting, and downstream use cases while driving platform evolution and engineering best practices (CI/CD, testing, documentation).

Design, build, and maintain scalable, fault-tolerant streaming data architectures and real-time pipelines using Kafka, MSK, and Kinesis. Implement stream processing, monitoring, security, IaC, and CI/CD. Collaborate with data teams, provide technical leadership, and optimize latency, throughput, and cost for real-time analytics and downstream systems.

In this role, you'll develop data pipelines, architect scalable data solutions using Snowflake, ensure healthcare compliance, and manage master data management initiatives.

Lead design and implementation of scalable data architectures and pipelines for real-time and batch processing; mentor junior engineers; ensure pipeline reliability, monitoring, security, and governance; collaborate with cross-functional teams and adopt new data technologies.

Lead the data engineering team to design, build, and scale data platforms and pipelines. Set standards, manage projects and technical debt, collaborate with stakeholders, drive adoption of new tools, ensure data governance, and provide technical leadership for complex data issues and real-time architectures.

The Data Engineer II will design, build, and maintain data pipelines, ensuring data governance and security. Responsibilities include coding in Python, managing data processing, and collaborating with data teams.

Lead data engineering for a healthcare scheduling platform rebuild: map legacy multi-TB schema, design target schema, build translation layer (views/materialized views and write mappers), ensure data consistency during parallel systems, plan per-tenant cutover with verification and rollback, tune DB performance, instrument data quality/lineage/audit, and mentor engineers.

Design and execute end-to-end SAP S/4HANA data migrations using LTMC, SLT, and LVM. Extract, transform, cleanse, validate, reconcile, and cut over master and transactional data. Optimize large-volume loads, support mock migrations and cutover runbooks, collaborate with functional teams, and maintain documentation and governance compliance.

Design, build, and maintain scalable data ingestion and egress pipelines using Airflow and dbt Cloud. Write Python for Airflow DAGs and utilities, model and transform healthcare datasets into analytics-ready formats with SQL and dbt, implement tests and monitoring, and collaborate with cross-functional teams to support data science and reporting needs.

As a Senior Data Engineer, you will build and optimize data pipelines, integrate AI capabilities, and collaborate across teams to create data-driven solutions, while providing technical leadership and ensuring data quality and governance.

The role involves building data platforms and pipelines, integrating AI solutions, and collaborating with product owners to address complex client issues.

Lead design and delivery of production data platforms, pipelines, and analytics. Architect Snowflake/Databricks solutions, build ETL/streaming ingestion, implement dbt transformations, data quality, observability, and governance, support BI and AI/ML feature/data pipelines, and mentor engineers while driving DataOps and platform best practices.

Design, build, and maintain scalable ELT/ETL data pipelines and data models on cloud platforms (preferably Snowflake). Enable batch and near-real-time integrations, ensure data quality/monitoring, create APIs and production-ready datasets for BI, analytics, and ML, optimize performance and cost, document architectures, evaluate new technologies, and mentor engineers.

The Senior Data Engineer will architect event-driven data pipelines, automate ETL processes, and ensure operational excellence in NVIDIA's financial infrastructure.

The Senior Data Engineer will oversee data operations, design scalable data pipelines, ensure data quality, and support cross-functional data initiatives.

The Senior Data Engineer will design and maintain data pipelines, write production-grade Python and SQL code, and support AI initiatives while collaborating across teams.

The Staff Data Engineer will lead the architecture and reliability of Hinge Health's data platform, manage technical complexity across teams, set data standards, and enhance engineering practices.

As a Senior Staff Data Engineer, you'll set the technical vision for data architecture, lead initiatives across teams, mentor engineers, and ensure platform reliability, while integrating data systems with ML pipelines effectively.

Design and build scalable batch and streaming data pipelines, lead architecture for Lakehouse platforms, and mentor junior engineers while optimizing data quality and performance.

As a Senior Data Engineer, you'll design and maintain data pipelines, collaborate with teams to optimize data processes, and provide mentorship to junior members.

Design and deliver scalable data solutions for analytics and reporting, involving hands-on data engineering and technical leadership, while ensuring quality and governance.

Design and develop Python-based analytics tools for investment research and portfolio analysis, while managing data lakes and AWS solutions.

As a Staff Data Engineer, lead significant data projects, ensuring scalable architectures and optimized data pipelines, while mentoring others and collaborating cross-functionally.