Top Data Engineer Jobs

Design and build scalable data solutions, develop real-time data pipelines, maintain ETL processes, and promote effective development methodologies.

As a Data Engineer, you'll create and maintain data pipelines, optimize data architecture, and support analytics tools for performance insights.

The Data Engineer will manage and develop data warehousing solutions, implement ETL processes, and utilize SQL for data analysis and reporting. Experience in analytics tools and communication is essential.

As a Data Engineer at Figma, you'll build and maintain scalable data pipelines, optimize data models, and collaborate with teams to ensure timely data delivery.

The Data Engineer will gather and process large datasets, develop algorithms, conduct data analysis, and improve predictive models for business decisions.

The Data Engineer will analyze data, optimize systems, and collaborate with data scientists and engineers, requiring strong SQL and PowerBI skills.

As a Data Engineer, you will build and optimize data pipelines, manage ETL workflows, and ensure efficient data access and quality within the infrastructure.

As a Data Engineer, you'll design and implement data lifecycle strategies, ensure data integrity, optimize solutions, and collaborate across teams to enhance data management.

As a Snowflake Data Engineer, you'll design, build, and maintain data infrastructure using Snowflake, focusing on governance, quality, and performance optimization. You'll collaborate with stakeholders to operationalize data use cases and implement key data strategies.

The Data Engineer will clean, manage, and analyze datasets, automate ETL processes, and collaborate with traders and software engineers to derive insights.

Lead design, build, and optimization of a Snowflake-centric cloud data platform and dbt transformation layers. Develop reliable pipelines from sources like Salesforce, ensure data quality, performance tuning, and compliance with PHI/PII/HIPAA. Collaborate with analytics, product, and engineering teams to deliver scalable, documented, analytics-ready datasets and platform standards.

The Data Engineer will enhance data pipelines, support data analysts, and optimize data architecture for cross-functional teams. This role involves data extraction, transformation, and analytics to meet reporting needs.

The Data Engineer will design, build, and optimize data pipelines, ETL workflows, and large-scale data solutions, with strong SQL expertise required.

The Data Engineer will manage data pipelines for financial institutions, translating raw transactions into insights while collaborating with various teams to enhance data models and tools.

The DBA/Data Engineer will manage PostgreSQL and MySQL databases, build scalable data pipelines, and integrate AI for automation, ensuring efficient data infrastructure.

Build and operate scalable data pipelines and analytics-ready datasets using Python, dbt, and BigQuery. Develop Looker dashboards, ensure data quality and observability, optimize performance and cost, integrate data workflows with backend services and CI/CD, and support analytics, experimentation, and production use cases.

Design, build, and maintain scalable ETL/ELT pipelines and data warehouse architectures. Automate ingestion, transform and validate data, enforce data governance, optimize queries, troubleshoot production issues, and collaborate with stakeholders to deliver timely BI and analytics solutions.

Design, implement, optimize, and maintain scalable, high-availability database solutions for a SaaS healthcare product. Integrate client data, resolve complex data issues, refactor systems for Azure, optimize MSSQL performance, participate in code reviews, and deliver features within Agile/Scrum to ensure reliable, high-performance data services.

Design, build, and maintain scalable finance-focused data pipelines and models; ensure data quality, manage migrations to modern stacks, monitor loads, troubleshoot issues, and collaborate with global teams and vendors to support reporting and analytics.

Lead design and delivery of enterprise data centralization and automation for reporting and BI. Build and maintain ETL/SSIS pipelines, data orchestration, file delivery and quality controls, follow SDLC/agile, mentor junior engineers, and partner with business stakeholders to capture requirements and ensure timely data delivery.

Lead modernization of core data systems and build scalable, secure data pipelines for cloud and on‑prem environments. Design data contracts, observability, lineage, and real‑time processing for vulnerability management. Partner with product and leadership to align data strategy and deliver customer-facing data solutions.

Build and maintain scalable batch and real-time data pipelines using Kafka, Google Dataflow, Snowflake and S3. Integrate APIs via Apigee, ensure data quality, publish data for reporting, and collaborate with stakeholders to document workflows and support analytics.

Design, build, and maintain scalable ETL/ELT data pipelines on Databricks and AWS S3; manage large geospatial and temporal datasets; productionize ML models; implement data validation, testing, and monitoring; optimize storage and processing; document workflows; collaborate cross-functionally.

Lead design, implementation, automation, and maintenance of large-scale ETL pipelines and scalable data solutions. Translate business questions into data requirements, validate and test datasets, mentor junior engineers, collaborate with analytics and stakeholders, and ensure robust, production-ready data solutions across global clients.

As a Senior Data Engineer, you will design and maintain data pipelines, define governance standards, and collaborate across teams to enhance Headway’s data architecture.