Top Data Engineer Jobs

Import, scrub, and manage client data; support reporting needs using SQL and BI tools; investigate error messages and system behavior; and provide customer-facing assistance requiring strong communication and professional acumen.

Build and optimize enterprise-scale Snowflake data solutions, including ingestion, ETL pipelines, transformation, quality assurance, production deployment, legacy warehouse migration, and workflow automation. Establish data governance, compliance policies, and data quality rules while supporting cloud-based architectures and efficient data consumption.

Develops scalable, secure ETL pipelines, database architectures, and real-time or batch data solutions. Integrates large datasets, ensures data quality and integrity, writes complex code and queries, and translates business needs into technical designs. Leads solution development, testing, releases, documentation, training, and vendor issue resolution while advising business partners on data analysis and tools.

Own and maintain the companys data infrastructure and pipelines. Design, build, and monitor ETL/ELT workflows and data architecture; integrate SaaS sources; enforce data quality, standards, and governance; partner with stakeholders to deliver analytics-ready data and meet data availability SLAs.

Designs scalable Databricks solutions and ETL/ELT pipelines while administering MariaDB and SQL Server environments. Responsibilities include database design, performance tuning, backup and disaster recovery, security and access management, data modeling, quality and lineage, and troubleshooting complex data issues. The role collaborates with stakeholders and technical teams, translates requirements into secure solutions, provides technical direction, and delivers demonstrations and training for Department of Transportation support.

Designs and operates an AWS-native lakehouse supporting analytics, reporting, visualization, and AI/ML. Builds batch and streaming ingestion pipelines using Python and PySpark, Apache Iceberg data structures, governance and metadata services, quality controls, security, observability, and CI/CD automation. Optimizes performance, scalability, reliability, and cost while collaborating with cross-functional technical teams and documenting architecture, operations, and secure configurations.

Supports secure data pipelines, ETL/ELT workflows, data transformations, and analytics-ready datasets in a classified DoD environment. Collaborates with data scientists, engineers, and mission stakeholders while using Python, SQL, Spark, Databricks, and comparable platforms. Performs data validation, modeling, quality practices, testing, documentation, and Agile development. The role is fully on-site in a SCIF at Camp Smith, Hawaii, and requires an active Top Secret/SCI clearance before starting.

Designs, builds, administers, and troubleshoots cloud data architectures, databases, schemas, metadata repositories, ETL processes, and analytic models. Ensures data integrity and quality, develops SQL queries and reports, leads testing and automation improvements, and supports dashboards, governance, data sharing, and metric collection. Collaborates with Agile teams to translate business requirements into technical infrastructure designs and decision-support capabilities using AWS, Java, Python or Scala, GitLab, and Terraform.

Designs and maintains data warehouses, semantic models, metrics layers, pipelines, dashboards, and certified datasets. Establishes KPI governance, data security, row-level access controls, quality standards, and observability. Builds Sigma, Power BI, and Databricks dashboards, supports self-service analytics, resolves BI issues, and enables AI/ML use cases. Collaborates with architecture, engineering, analysts, and business stakeholders to define requirements, document solutions, train users, and drive BI adoption.

Designs, builds, deploys, and maintains scalable data platforms, warehouses, lakes, ETL/ELT pipelines, and batch or streaming workflows. Optimizes cloud data lake and pipeline performance, manages data governance and lifecycle solutions, and collaborates with multidisciplinary agile teams. The role supports mission-driven client projects involving disparate structured, unstructured, and event-streaming data.

Designs, builds, and maintains scalable data pipelines, infrastructure, data models, dashboards, and visualizations. Collaborates with data scientists, analysts, and stakeholders to improve data quality, accessibility, security, and decision-making. Analyzes workflows and data patterns, contributes to coding standards, supports cloud data integration and warehousing practices, uses AI tools, and grows into deployment and support rotations.

Design, build, and maintain scalable data pipelines, data lakes, and databases; ingest and map customer financial datasets; monitor pipeline reliability; translate business requirements into data flows and analytical insights to ensure high-quality, usable data.

Build and maintain data pipelines to ingest, normalize, and deliver messy healthcare data (FHIR, HL7, CCDAs, PDFs) into structured models for AI and clinical use. Implement ETL, real-time webhooks, document extraction, PII sanitization, storage on AWS, and monitor data quality while ensuring compliance with healthcare interoperability standards.

Design, build, deploy, and operate production-grade data pipelines and products for healthcare and marketing datasets. Implement data models, Airflow workflows, data-quality controls, and PHI/PII privacy controls. Collaborate with product, analytics, and platform teams to support audience discovery, segmentation, activation, measurement, and reporting.

Build, deploy, and operate production-grade data pipelines and data products for healthcare audiences. Design transformations, data models, and governed views using Python, SQL, Airflow, S3, Snowflake, and EMR. Implement data-quality, monitoring, and privacy-by-design controls for PHI/PII. Partner with product, analytics, and platform teams to onboard sources, support audience discovery, segmentation, activation, measurement, and troubleshoot production issues.

As a Quantitative Developer, you'll innovate and enhance quantitative methods, develop custom tools, maintain data pipelines, and collaborate with researchers for advancing investment strategies.

The Principal Data Engineer will lead the technical strategy for data initiatives, focusing on real-time data platforms and collaboration with stakeholders to design efficient and innovative data architectures, ensuring data governance and compliance.

As a Data Engineer, you will design, implement, and maintain data systems for Notifications at Whatnot, ensuring data quality and performance while collaborating with cross-functional teams on data architecture and workflows.

Support and improve enterprise data platforms by monitoring and troubleshooting ETL workflows, resolving production incidents, conducting root cause analysis, deploying enhancements, coordinating source-system changes with vendors and technical teams, tuning database and server performance, managing capacity, and maintaining operational documentation and stakeholder communications.

Design, implement, and optimize large-scale data processing on Databricks and Spark. Build ETL pipelines, integrate data across AWS services (Redshift, RDS), orchestrate workflows with Airflow, and ensure data warehousing and engineering best practices. Lead and mentor development teams and collaborate with cross-functional stakeholders to drive data strategy and execution.

As a Data Engineer at PNC, you will design, build, and maintain robust OLTP databases, ensuring high availability and strong performance while collaborating with cross-functional teams to manage data integrity and security.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.

As a Senior Lead Data Engineer at Capital One, you'll lead a development team, utilizing various big data and cloud technologies to deliver impactful solutions. Responsibilities include collaborating with Agile teams, mentoring, and ensuring optimal code performance.

Lead design and scaling of the data platform and analytics pipelines. Build and maintain ETL/ELT workflows, integrations, serverless data services, and reliable data models. Mentor teammates, improve automation, observability, and data governance to support analytics and operational insights.

Design, build, and operate end-to-end ELT data pipelines on Azure/Databricks. Implement DLT data quality checks, CDC, schema evolution, dimensional models for Power BI, monitoring, CI/CD, and operational runbooks while partnering with architects and BI stakeholders.