Top Data Engineer Jobs

The Principal Data Engineer will design and implement scalable data platforms, lead architecture discussions, and mentor teams. Requires expertise in Azure and Databricks.

Design and implement scalable, secure enterprise geospatial database solutions using Esri technology. Collaborate across project phases to configure, maintain, tune, secure, and automate databases, support ArcGIS applications, and provide technical guidance for migrations, integrations, and operational readiness for Defense/Intel clients.

Consult with customers to design and implement enterprise geospatial database solutions using Esri/ArcGIS technologies. Configure, secure, monitor, and automate databases (backup/HA/DR, performance tuning, data loading). Collaborate across teams, provide technical guidance, and support database migrations and integrations for mission-critical defense and intel applications.

Consult with customers to design and implement scalable, secure enterprise geospatial database solutions using Esri/ArcGIS technologies. Configure and maintain database environments (backup, HA/DR), monitor and tune performance, implement security and access controls, automate data workflows, and provide technical guidance across requirements, design, build, and deployment phases. Support integration with ArcGIS web, desktop, and mobile applications for Defense and Intel clients.

The Data Engineer will analyze data quality, design prediction algorithms, collaborate with the engineering team, and generate business 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.

The Data Engineer will develop data pipelines and integrations, focusing on healthcare data to enhance financial operations, ensuring efficient data handling and driving impactful solutions.

Design, build, and manage batch and real-time data pipelines on GCP. Implement Terraform IAC, CI/CD, APIs, and CDC ingestion via Datastream. Build medallion architecture with Dataform/dbt, optimize BigQuery and ClickHouse models, create Airflow DAGs with monitoring, and maintain GDPR/CCPA compliance and data governance.

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

Build, maintain, and optimize ETL/ELT data pipelines using Databricks, Apache Spark, and SQL. Support data ingestion, transformation, SSIS integration, and SQL Server development. Troubleshoot data quality, assist production support, document processes, and collaborate with analysts and stakeholders. Support data governance, HIPAA compliance, and healthcare data initiatives.

The role involves designing and scaling data infrastructures for private equity, developing ETL/ELT pipelines, ensuring data quality, and collaborating with various teams on data governance.

The Data Engineer will develop secure, scalable data pipelines for IRS applications, supporting complex analytics and machine learning to combat fraud and ensure compliance. Responsibilities include pipeline engineering, troubleshooting, and collaboration with data teams to create production-ready analytics solutions.

The Cloud Data Engineer will design and develop data warehouse solutions, create efficient data pipelines, collaborate with teams, and monitor system health.

The DMS Data Engineer is responsible for analyzing raw data, building data systems and pipelines, conducting complex data analyses, and collaborating on projects to enhance data quality and reliability.

The Data Engineer will design and develop data pipelines for quality monitoring, assess data integrity, and build web applications supporting user validation and analysis.

Build and maintain ETL/ELT pipelines in a lakehouse/cloud environment, ensure data quality and lineage, and apply classical statistics and ML (anomaly detection, regression, time-series) to support operational decision-making and stakeholder reporting.

Designs, builds, and maintains scalable batch and streaming data pipelines, ETL/ELT workflows, data models, and Python transformations. Writes optimized SQL, monitors pipeline reliability, troubleshoots failures, implements data-quality validation, and supports security and governance practices. Collaborates with engineers, analysts, stakeholders, and clients to define data contracts, improve platforms, document lineage, and deliver reliable analytics data.

Administer, maintain, and optimize SQL and NoSQL database environments; apply data warehousing concepts; perform data management and maintenance using SQL, Python, and Apache Spark; support cloud database infrastructure with Git, AWS, or Azure; and provide database support for Tableau and Power BI reporting.

Administer, maintain, and optimize SQL and NoSQL database environments. Apply data warehousing and data management practices, using SQL, Python, and Apache Spark. Support database infrastructure with Git and AWS or Azure, and provide database support for Tableau and Power BI reporting and visualization tools.

Design, build, and maintain large-scale data pipelines and DAGs (Airflow) that process imagery, LiDAR, and other sensor data. Improve platform reliability, observability, resource tuning, and Kubernetes deployments. Collaborate with ML, hardware, and full-stack teams; own pipeline design, implementation, testing, and operations in a hybrid NYC role.

The Cloud Data Engineer designs and supports scalable Snowflake and Azure data architectures, environments, and ETL/ELT pipelines. Responsibilities include Snowflake performance and cost optimization, Azure resource management, security controls, troubleshooting, documentation, design reviews, and collaboration with architecture, engineering, BI, and security teams. The role also contributes to software development, testing, debugging, mentoring, and data warehouse and data mart implementation.

Develops and manages data pipelines with Snowflake, SQL, dbt, and Airflow; builds REST APIs and microservices using Python and FastAPI; supports Salesforce Data Cloud; implements CI/CD; creates reusable Slack app frameworks; and collaborates cross-functionally on scalable solutions.

Design, build, maintain, and optimize Spark and Scala ETL/ELT pipelines on AWS for terabyte- and petabyte-scale datasets. Work across S3, Snowflake, Kafka, and monitoring systems, resolve production data-quality and performance issues, write automated tests, participate in architecture and code reviews, and support on-call operations. Use generative AI to improve pipeline development, monitoring, and engineering productivity.

Designs, develops, tests, deploys, and supports batch and streaming data pipelines using Azure and Databricks. Builds ETL/ELT processes, optimizes data workflows, supports cloud modernization, and performs monitoring, troubleshooting, and root cause analysis. Collaborates with business and technical teams on requirements, data governance, lineage, and audits. Mentors junior engineers and communicates solutions to technical and non-technical stakeholders.

Build and maintain scalable production data pipelines, infrastructure, warehouse models, analytics platforms, and data-quality systems. Partner with software engineers to instrument product features and ensure reliable event data. Support Hex and Snowflake self-serve analytics, maintain business metrics and data logic, and develop monitoring, validation, alerting, and observability tooling. The role also collaborates with product, analytics, marketing, and engineering teams, with potential future exposure to recommendation and LLM-based product work.