Top Data Engineer Jobs

The Data Engineer will develop and integrate data pipelines, ensure data integrity, and support continuous automation in an Agile/Scrum environment.

Lead design and implementation of a cloud-based data platform using AWS/Azure and AI capabilities. Gather requirements, deliver production-ready DevSecOps solutions, mentor engineers, build data pipelines, integrate COTS/APIs, and translate strategy into technical roadmaps to enable data-driven decision making.

Operate and support critical data pipelines and infrastructure, troubleshoot production data issues, perform root cause analysis, implement automation and monitoring, own incident management and on-call rotation, and create support documentation to ensure reliable, timely, and consumable data for stakeholders.

Lead and mentor a data engineering team to design and operate scalable ETL/ELT pipelines and Snowflake data warehouse solutions using Python, DBT, Matillion, and AI tools; establish standards, ensure data quality and governance, and collaborate with analytics, product, and BI stakeholders to deliver production-ready data platforms.

The Data Engineer will design, build, and maintain analytics-ready Data Marts, create resilient data pipelines, and ensure data integrity, working closely with analytics teams to deliver reliable datasets.

The Data Engineer supports supply chain outcomes by building and maintaining data pipelines, designing data transformations, and collaborating with stakeholders to improve order-to-cash processes.

The Data Engineer will manage, optimize, and expand data infrastructure for a clinical data registry, focusing on building automated data pipelines and supporting healthcare advancements through data insights.

The Data Engineer I is responsible for building reliable ELT/ETL pipelines, implementing data quality checks, and optimizing data models using dbt, while collaborating with stakeholders to ensure data reliability and consistency.

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.

The Senior Data Engineer will manage data flow and ensure accuracy, improve data engineering stacks, build and maintain analytics warehouses, and support stakeholders with data solutions while participating in system reliability on-call rotations.

As a Senior Data Engineer, you will design data pipelines, manage databases, optimize data workflows, ensure data integrity, and collaborate with cross-functional teams on data-driven solutions.

The Staff Data Engineer will build and manage a data lake, optimize data pipelines, collaborate with teams, and support AI projects while ensuring quality data solutions.

Design and develop data models and pipelines, optimize data systems, collaborate with teams, enforce data governance, requiring 5-7 years of data engineering experience.

The Founding Data Engineer/Data Scientist will design and build data systems for payments and fraud, ensuring data accuracy and enabling analytics. Responsibilities include establishing data pipelines, models, quality checks, and documenting processes while collaborating with stakeholders.

The Data Engineering Intern will assist in building data pipelines, support ETL workflows, ensure data quality, and document processes using SQL and Python.

As an FP&A Data Engineer, you will manage data pipelines, develop financial models, and automate reporting to assist management and teams in making data-driven decisions.

The Data Modeler will design and maintain data models, support data architecture, collaborate with product teams, and ensure quality and governance of data products.

The Data Engineer will architect and optimize data systems for aviation data, focusing on flight test data processing and predictive maintenance analytics.

The Data Engineer will maintain and optimize data pipelines, manage infrastructure, support ML workflows, and collaborate with teams on data products.

The role involves writing and deploying scripts for data collection, transforming data sets, diagnosing bugs, and collaborating with other engineers using agile principles.

As a Data Engineer, you will develop strategies, metrics, tools, and models to assess and optimize Starlink's customer acquisition, leveraging data insights to enhance business operations.

The role involves owning the data infrastructure and pipeline, building robust data pipelines, managing Snowflake and dbt, and delivering analytics and dashboards.

The Data Engineer designs and builds AI-driven solutions, optimizes data pipelines, manages integrations, and enhances analytics capabilities across the organization to improve efficiency and decision-making.

The Senior Data Engineer will build and maintain data pipelines, work with cross-functional teams, and optimize performance using various data processing tools.

The Data Engineer will develop data pipelines, advise clients on cloud technologies, and collaborate with teams to maximize data architecture for decision-making.