Top Data Engineer Jobs

Lead architecture and implementation of fleet telemetry, time-series storage, streaming pipelines, and CRM/warehouse integrations on AWS. Build tools for proactive fleet health, partner cross-functionally (firmware, manufacturing, ops), support on-call as systems mature, and design LLM-driven automations to increase team leverage.

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.

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

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.

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 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.

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

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

Lead and mentor multiple Databricks-focused data engineering teams, define engineering best practices and reusable frameworks, drive CI/CD and performance/cost optimization, build and support analytical and streaming pipelines, and collaborate with architects, product owners, and cross-functional partners to deliver high-quality data products.

Design and build enterprise-scale Snowflake environments, develop and optimize data pipelines with Python, dbt, and Airflow, lead client technical strategy, implement Snowflake security/compliance, and mentor junior engineers while collaborating with Snowflake, AWS, and Anthropic partners.

Design, build, and optimize the company lakehouse environment and ETL/ELT pipelines (Databricks/Azure/Fabric). Develop semantic models, governed metrics, data quality controls, monitoring, and CI/CD practices. Partner with business, security, and analytics teams to steward master data, implement governance and access controls, and enable reliable datasets for reporting and AI use cases.

Own and improve the company data stack: expand the data warehouse, build and streamline Python-based ingestion and ETL processes, refactor dbt models, maintain data quality, standardize reporting, and collaborate with engineering and analysts. Act as technical owner for parts of the stack and proactively drive improvements and automation.