Top Data Engineer Jobs

As a Senior Data Engineer, you will design, build, and maintain scalable data platforms, ETL pipelines, and support analytics and ML workflows, ensuring data quality and cross-functional collaboration.

The role involves designing and implementing ETL solutions for data integration, conducting testing, and collaborating on data models and architecture documents for a client.

The Senior Data Engineer will develop data engineering solutions, manage ETL workflows, and establish a new data practice while collaborating with stakeholders.

The Senior IT Big Data Developer will design and optimize data architectures, develop ETL/ELT pipelines, support data integration, and ensure compliance with data governance standards.

The AI-Native Data Platform Engineer will design data foundations for AI systems in wealth management, architecting data pipelines, models, and frameworks to enable autonomous financial agents.

The Data Architect will design scalable data models, transform raw data into actionable insights, and deploy analytics solutions for healthcare providers, with a strong emphasis on SQL proficiency and cloud technologies.

Design, build, and maintain scalable ETL/ELT data pipelines and analytical platforms on AWS and Databricks. Migrate legacy workflows to cloud-native services, implement data lake and catalog solutions, enable AI/RAG/vector search, ensure FedRAMP/NIST compliance, optimize performance, and mentor junior engineers while collaborating in Agile teams.

The Senior Data Engineer will design and operate the data platform, build ELT/ETL pipelines, optimize data performance, and ensure data quality while collaborating with business teams.

The Senior Data Engineer designs scalable data solutions to harmonize data across various ERP systems, implementing ETL/ELT pipelines and ensuring data quality and governance.

Design, develop, and execute enterprise CRM data migrations into Microsoft Dynamics CRM/365 using KingswaySoft and SSIS. Extract, transform, cleanse, validate, and load structured and unstructured data from legacy systems, optimize SQL/SSIS, troubleshoot performance, support integrations and customizations, perform validation testing and production cutovers, and document migration architecture and procedures while ensuring data governance and security compliance.

As a Staff Data Engineer on the Data Lake team, you will architect, build, and scale distributed ETL pipelines, ensuring data quality and leading the engineering team. You will also drive large-scale data processing and technical initiative leadership.

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

The Senior Data Engineer will design and maintain data pipelines and infrastructure for fraud detection analytics, ensuring data integrity and supporting testing across platforms.

Lead design and implementation of batch and streaming data pipelines, build data models, implement data quality and testing, manage orchestration and IaC, mentor engineers, and communicate technical direction and tradeoffs to stakeholders.

The role involves developing and integrating cloud-native data services and APIs, supporting data transformation, and maintaining backend services using AWS technologies.

The Sr. Data Engineer will build and manage data pipelines for large datasets, collaborate with teams, and leverage cloud technologies for data processing.

Lead Data Engineer responsible for defining architecture, engineering standards, and best practices for the enterprise data platform, collaborating with distributed teams for modernization and scalability.

Design, build, and maintain scalable data pipelines, ETL/ELT processes, data lake and warehouse infrastructure, and cloud-based data platforms. Optimize systems for performance, reliability, security, and cost while implementing monitoring, governance, and data quality practices. Collaborate cross-functionally with data scientists, analysts, engineering, and product teams to deliver reliable data solutions and improve the data ecosystem roadmap.

Build and maintain data warehouses, pipelines, scalable data models, and data quality frameworks for Waymo commercialization. Translate business requirements into database models, transform raw data for reporting and insights, ensure PII and ACL compliance, document solutions, and collaborate with data producers and consumers. The role requires SQL expertise, database knowledge, and programming experience in Python, C++, or Java, with preferred experience in distributed data processing and cross-functional project leadership.

Designs and delivers a global analytics platform supporting reporting, visualizations, self-service analytics, and embedded data products. Responsibilities include data collection and processing, semantic modeling, warehouse and pipeline development, query optimization, governance, analytics enablement, and stakeholder collaboration. The role provides actionable insights from complex travel data and builds integrated analytics applications using cloud platforms and business intelligence tools.

Designs, builds, tests, and maintains software and data infrastructure for business-facing solutions. Develops CI/CD and DevOps practices, supports applications throughout their lifecycle, contributes to internal tools and standards, and collaborates directly with end users. Requires Python, SQL, large-scale data engineering experience, Azure and Databricks knowledge, and familiarity with Power BI, Copilot Studio, and AI tools.

Designs and maintains scalable data pipelines and platforms, develops ETL/ELT processes, and migrates heterogeneous external data into standardized enterprise models. The role includes data ingestion, transformation, quality validation, reconciliation, and billing-data standardization across systems. It collaborates with engineering, product, DevOps, and DBA teams, contributes to technical decisions, mentors engineers, and applies AI-assisted development tools. The position is based in Richmond, Virginia, with four days in office and one day remote.

Own Doctronic’s end-to-end data platform, including CDC pipelines from production databases into S3, Iceberg, and Snowflake; dbt transformations; orchestration; warehouse architecture; monitoring; and governed access to PHI. Establish trusted, documented data layers for analytics, finance, dashboards, and AI model training. Implement HIPAA-compliant access controls, anonymization, and deletion workflows while partnering autonomously with product, finance, marketing, partnerships, and AI teams.

Designs, builds, and maintains scalable AWS data pipelines, integrations, lakehouse infrastructure, and Airflow workflows. Processes commercial pharmaceutical data, supports pharma KPIs and analytics, and develops pipelines for AI, machine learning, generative AI, LLM, embeddings, and RAG applications. The role also includes legacy-system migration, pipeline monitoring and optimization, data quality assurance, and translating pharmaceutical business needs into reliable data solutions.

Design and implement end-to-end AI features, scalable data pipelines, ETL/ELT workflows, Generative AI and agentic systems, ML and BI solutions, and MLOps/LLMOps practices across AWS, Azure, and GCP. Apply RAG, embeddings, vector databases, security governance, evaluation, reliability, and guardrails. Own technical workstreams, mentor junior engineers, and promote software engineering best practices in consulting environments.