Top Data Engineer Jobs

The role involves designing and managing data pipelines, developing canonical datasets, and ensuring data integration and compliance. Collaborate across teams to meet data needs and maintain data architecture.

The Senior Data Engineer will design, develop, and maintain data platforms, create ETL processes, handle data quality issues, and mentor teammates while ensuring scalability and performance in data solutions.

Design, build, and own data infrastructure and ETL/ELT pipelines (Airflow, S3, Lambda) into a governed Snowflake warehouse. Implement data quality, IaC (Terraform/CDK), CI/CD, and analytics solutions (SQL, Tableau). Enable ML/LLM use cases like forecasting and anomaly detection and deliver automated reporting and data-driven marketing outputs.

Design, build, and maintain scalable data pipelines and tenant-aware APIs to ingest and transform data from varied sources. Work with event-driven and batch architectures, implement authentication and integration patterns, ensure observability/monitoring, optimize data flows for cost and performance, and collaborate with product, infrastructure, and engineering teams to onboard and maintain data sources at scale.

Partner with stakeholders to define metrics and deliver dashboards and insights. Build and optimize data models in Amazon Redshift, design and maintain scalable ETL pipelines using Python and Apache Airflow, monitor data quality and pipeline performance, and participate in code reviews and engineering best practices to support analytics and reporting needs.

Lead architecture and implementation of an AWS-native data platform powering analytics, ML, and AI workflows. Build scalable ETL/ELT pipelines (Airflow, Fivetran, dbt), enforce governance, observability (Datadog), and data quality, and provide technical leadership across Data Science, Analytics, Product, and Engineering.

Design and build scalable cloud data pipelines for high-volume manufacturing and IoT data. Bridge OT/IT systems for real-time extraction using industrial protocols, implement medallion/lakehouse architectures on Databricks/Snowflake/AWS/Azure, and apply analytics and lean methodologies to improve yield, uptime, and efficiency.

Build and maintain scalable ETL pipelines using Python, Spark, and Airflow; collaborate with AI/ML and Product teams to deliver AI-native data products; identify and resolve ETL bottlenecks; ensure code quality through reviews and tests; own sprint deliverables and contribute to roadmap planning and major epics.

Lead engineering strategy and hands-on implementation for Finance & Actuarial data platforms. Architect no-touch automated data pipelines, drive cloud migrations (Azure Synapse/Databricks/Snowflake), embed AI-assisted development and modern DevOps, establish CI/CD and runbooks, resolve complex incidents, evaluate tooling, and mentor engineering squads while communicating strategy to executive stakeholders.

Design and implement scalable AWS-based data infrastructure using Spark and Scala. Build fault-tolerant batch and streaming pipelines, optimize storage formats and engines, collaborate with Data Science and Product, implement automated data quality checks, and deliver performant data assets and APIs.

Design and implement scalable data infrastructure in AWS using Spark and Scala. Evolve core data pipelines, store data in optimal engines/formats, build knowledge graphs and APIs, optimize AWS resources, implement automated data quality checks, and collaborate with Data Science and Product teams to deliver reliable, large-scale data services.

Design and implement scalable data infrastructure and pipelines on AWS using Spark and Scala. Build fault-tolerant batch and streaming workflows, optimize storage formats and engines, enforce automated data quality checks, and collaborate with Data Science and Product teams to deliver reliable data assets and APIs.

Design, build, and optimize scalable data infrastructure and pipelines on AWS using Spark/Scala. Store and model data in appropriate engines and formats, implement knowledge graphs accessible via batch jobs and APIs, enforce automated data quality checks, and collaborate with Data Science and Product teams to deliver performant, cost-effective data services.

Seeking a Senior BODS Developer to develop and maintain complex BODS processes for data transformation. The role includes improving data quality using Information Steward and GAC/URAC techniques, collaborating with teams, creating documentation, and mentoring others.

The Lead Data Engineer at Lennar will design and implement data engineering solutions, lead the data platform team, and ensure data quality and accessibility for business insights.

As a Data Platform Engineer, you'll design and maintain scalable data systems, partner with teams on product direction, and ensure system reliability and security.

The Sr. Data Engineer will develop KPIs for infrastructure costs, analyze data, create reports, and enhance data systems for Starlink's ground network.

Design and implement Lakehouse solutions and data pipelines, optimize Databricks environments, and integrate AI applications while delivering exceptional results for clients.

Lead design and delivery of Databricks-based Lakehouse solutions and end-to-end data engineering projects. Build and optimize ETL, streaming and batch pipelines, integrate cloud and on-prem systems, mentor team members, support pre-sales, and ensure governance, security, and platform performance.

The Senior Data Engineer will design and implement complex data models, collaborate on data governance, lead data initiatives, and mentor team members.

The Senior Data Engineer will design and optimize data pipelines and services, leading development in Azure environment, collaborating with teams for high-quality data solutions.

The Data Engineer will design and maintain scalable data pipelines, automate workflows, and enhance data governance while collaborating with cross-functional teams.

As a Staff Data Engineer, you'll oversee Gamma's data infrastructure, architect scalable systems, mentor engineers, and drive strategic decisions for data usage across the organization.

Own and evolve the data platform by leading architectural evolution, collaborating with teams for strategic data initiatives, and ensuring reliable data systems.

Design, develop, and maintain large-scale data architectures and pipelines; deploy cloud-native data applications and CI/CD; support ML model productization; enforce code hygiene and best practices; mentor junior engineers; produce documentation and runbooks; collaborate with consulting teams and clients and travel as required.