Top Data Engineer Jobs

Design and implement a financial knowledge graph architecture, build graph ingestion and transformation pipelines, apply graph algorithms and analytics, define best practices, drive adoption across teams, and mentor/hire engineers to scale the platform while collaborating with investment and compliance stakeholders.

Designs and operates data-driven solutions supporting intelligence requirements. The role develops data architectures, integration models, automation, algorithms, and software tools; collaborates with GEOINT analysts; manages data governance and metadata; interrogates databases with SQL; and applies data science libraries to large-scale intelligence analysis. It requires substantial intelligence and GEOINT experience, advanced technical expertise, strong communication skills, U.S. citizenship, and an active TS/SCI clearance.

Designs, builds, and operates scalable batch and real-time data infrastructure processing trillions of data points. Responsibilities include platform architecture, infrastructure as code, self-healing systems, observability, developer tooling, pipeline optimization, security controls, database tuning, and distributed-system troubleshooting. The role collaborates with engineering and product teams, improves reliability and performance, and enables safe access for data engineers, software engineers, and AI agents.

Design, build, and maintain scalable data pipelines and platforms to ingest, merge, and prepare structured and unstructured data for analytics and AI. Lead multidisciplinary teams, perform data exploration and statistical analysis, and support use of LLMs/GenAI to enable mission-driven solutions across fraud detection, healthcare, and intelligence domains.

Build and operate large-scale data ingestion pipelines powering research and trading platforms. Own pipeline quality, reliability, performance, and data health; collaborate with traders, quantitative researchers, and data owners; optimize compute, storage, and SLAs; migrate pipelines to modern platforms; and implement tools to detect and resolve source-data quality issues.

Design, build, and operate Databricks Lakehouse pipelines and Delta tables. Optimize Spark/SQL workloads, implement incremental/CDC patterns, ensure data quality, deliver documented datasets and dashboards (Power BI), and collaborate with stakeholders to meet SLAs while supporting data-driven decisions.

The candidate will improve the data ETL pipeline, build analytical tools, manage operations, and expand into new markets and asset classes.

Build and operate ingestion and transformation pipelines to turn messy insurance data into clean datasets. Design bronze/silver/fact layers, model and tune Postgres and analytical stores, define KPIs and reconciliation checks, orchestrate observable data jobs, and ensure end-to-end data quality for analytics and AI products.

Lead design, build, and support of scalable data pipelines and integrations using Microsoft Fabric, ADF, PySpark, SQL, ADLS Gen2, and Databricks Unity Catalog. Drive Azure-to-Fabric migration, stabilize pipelines, tune performance, manage data governance, troubleshoot issues, document designs, mentor team members, and collaborate with stakeholders in Life Sciences regulatory environments during US Eastern hours.

Designs, builds, and maintains scalable batch and streaming data pipelines, data warehouses/lakes, and ETL/ELT processes. Collaborates with BI, Data Science, and Architecture teams to model data, validate sources, ensure data quality, optimize performance, and enable analytics using cloud and big-data technologies (AWS, Snowflake, Databricks, Spark, Kafka).

The Data Engineer will design and manage data pipelines, develop datasets for product metrics, and collaborate with teams to ensure robust data integration and processing.

Design and implement SQL transformations and datasets, manage data models in Databricks, optimize performance, and ensure compliance with data governance standards.

Lead architecture, systems, and roadmap for Coinbase's Compliance Reporting Data Platform. Design and build production-grade data models, pipelines, quality frameworks, validations, and certification processes. Establish data contracts, monitoring, reconciliation, and audit-ready processes. Partner with engineering and compliance stakeholders, respond to regulatory exams, and mentor engineers while shaping standards and documentation.

Build and maintain complex data pipelines in Azure Synapse using Spark, Python, SQL, and C#. Apply data warehouse and lakehouse modeling standards, support analytics and machine learning initiatives, ensure data quality, and collaborate with analysts. Mentor junior data engineers, review code, establish team guardrails, and guide execution while following software development lifecycle standards.

Design, build, and maintain ETL pipelines and big-data workflows from ingestion to consumption. Troubleshoot data/system issues, work in an agile team, handle structured/unstructured data and security logs, and support government data acquisition and sharing while meeting quality assurance and testing standards.

Lead design and implementation of a scalable Big Data Audience Management platform (500+ TB). Own data pipelines (ingest, validation, transformation, storage) using Spark and Scala, mentor engineers, perform R&D on new technologies, and partner with product managers to meet roadmap and business needs.

Senior ETL Data Developer to design, build, test, and support Epic Clarity and enterprise ETL solutions using SSIS (and DataStage). Develop and optimize ETL workflows, implement standards, troubleshoot complex integration issues, document designs, and collaborate with reporting, analytics, and business teams to deliver data warehouse solutions and integrations.

Design, implement, and maintain scalable data infrastructure and real-time processing for analytics platforms. Migrate systems from AWS to on-prem Kafka/Spark, implement data transformations, support production, optimize pipelines, query and analyze data, and build scripts and APIs to operationalize data science work.

The Data Engineer will support Data Analytics and Business Intelligence efforts, developing data pipelines, ensuring data performance, and collaborating within Agile frameworks to meet complex requirements for federal clients.

The Data Engineer will develop data pipelines, support data automation, collaborate with Agile teams, and ensure data reliability and performance. The role requires strong ETL skills and experience with relational databases, big data analysis, and CI/CD practices.

The Data Engineer will develop data pipelines, manage complex data sets, and ensure data reliability while collaborating within an Agile/Scrum team.

The Data Engineer will develop data pipelines, support Agile team collaboration, ensure data extraction performance, and promote process automation.

The Data Engineer will develop data pipelines, support Agile teams, ensure data performance, and collaborate to implement complex requirements for federal customers.

The Data Engineer develops data pipelines, supports Agile teams, ensures data performance, advocates for lean practices, and collaborates across functions to deliver insights for federal customers.

The Data Engineer will develop data pipelines, ensure data reliability, and support process automation while collaborating within Agile teams.