Top Data Engineer Jobs

Designs, develops, tests, and maintains data engineering processes, including data models, mappings, ETL pipelines, metadata structures, data quality rules, and data profiling. Analyzes source and target data, supports analytical and data science outcomes, evaluates downstream impacts, and recommends solutions. The role also requires automation, data governance, and post-deployment support using agile methodologies.

Design and lead scalable, secure, highly available database infrastructure for multi-terabyte SQL Server environments. Set technical direction for data architecture, performance, real-time pipelines, security, and growth. Troubleshoot complex production issues, optimize queries and indexes, guide cross-functional projects, mentor engineers, review changes, reduce technical debt, and evaluate emerging technologies. Monitor database health using Splunk, Datadog, and Grafana while influencing engineering and Site Reliability strategy.

Build and operate a large-scale enterprise data platform spanning batch and streaming processing, lakehouse storage, Kafka infrastructure, APIs, observability, and agentic MCP interfaces. Develop reusable ingestion and data-quality frameworks, improve scalability and resilience, establish engineering practices, support production operations, and mentor engineers. The role requires deep ownership of distributed data infrastructure and practical use of AI coding agents.

Design and operate production-grade data pipelines, backend services, APIs, and agentic AI workflows. Build scalable systems that ingest, transform, and operationalize data for customer-facing and internal applications. Translate ambiguous operational workflows into reliable architectures, improve service observability and performance, and own technical decisions across data modeling, system design, security, and compliance.

Design and develop scalable data pipelines, data models, schemas, and integrations for a video advertising platform. Collaborate across engineering, define user stories, deliver features using AI-assisted tools, write unit tests, maintain code quality, and support production systems on a rotating schedule. The role requires strong SQL, ETL/ELT, dbt, Airflow, Snowflake, AWS, and data architecture expertise.

Design and implement scalable data solutions using Microsoft Fabric and Azure. Build and orchestrate ETL/ELT pipelines, develop Power BI reports and DAX, optimize T-SQL and KQL queries, model data for Lakehouse/warehouse architectures, integrate varied data sources with Spark/PySpark, automate processes, ensure governance and security, and troubleshoot pipeline issues.

Leads the enterprise data architecture strategy, designing scalable platforms for secure data exchange, onboarding, discovery, and consumption. Establishes architecture standards, roadmaps, and engineering practices while adopting modern data and AI technologies. Partners with executives and global engineering teams, influences technical decisions, ensures governance and compliance, and mentors teams. The role requires deep expertise in large-scale data platforms, distributed systems, cloud and on-premises environments, and enterprise integration.

Design and build maintainable data pipelines, ETL processes, and data architecture standards. Collaborate with product managers, analysts, and machine learning engineers to translate requirements into automated, scalable solutions. Apply software engineering best practices, asynchronous systems, APIs, streaming, testing, monitoring, and Python and SQL expertise. Help prioritize data initiatives based on business impact and communicate complex technical concepts to technical and non-technical stakeholders.

Design, build, and scale reliable data infrastructure, including event ingestion, stream processing, data warehouses, ETL pipelines, analytics tools, and machine learning systems. Optimize performance, reliability, security, and data quality across AWS regions and data centers. Collaborate with analytics and data science teams, troubleshoot complex systems, influence architecture, conduct code reviews, and mentor data engineers while helping establish engineering best practices.

Designs and delivers scalable data engineering, analytics, automation, AI-enabled solutions, and supply chain applications. Builds Python solutions, Snowflake data pipelines, data models, reporting, and self-service analytics supporting planning, procurement, logistics, forecasting, inventory optimization, and operational decision-making. Partners with business and technical teams to translate requirements into reliable solutions, improve processes, maintain data quality, and provide technical leadership across analytics and data engineering initiatives.

Design, build, and own scalable data infrastructure for proteomics research and machine learning. Responsibilities include developing production data platforms and pipelines, integrating instruments and LIMS, creating cloud infrastructure with infrastructure-as-code and CI/CD, ensuring data integrity and lineage, and transforming raw experimental data into reliable ML-ready datasets. The role partners closely with scientific teams, establishes engineering standards, sets technical direction, and mentors colleagues.

Design, build, and own scalable data infrastructure for proteomics research and machine learning. Develop production data platforms, automated workflows, cloud infrastructure, pipelines, lakehouse architectures, and integrations with instruments and LIMS. Establish data integrity, lineage, security, and reproducibility standards while partnering with scientific teams. Set technical direction, operate terabyte-scale systems, review designs and code, and mentor colleagues.

Designs, develops, and operates production data pipelines and curated, AI-ready data products for AbbVie R&D. Responsibilities include data integration, normalization, modeling, metadata, lineage, quality controls, governance, documentation, knowledge graph publication, and support for RAG and vector-search workflows. The role collaborates with scientists, engineers, architects, data owners, and vendors; provides technical guidance; monitors pipeline reliability; resolves issues; and ensures compliance with data security, GxP, and regulatory standards.

Designs, builds, deploys, and maintains scalable cloud-native data platforms and pipelines in AWS. Supports data acquisition, preparation, database architecture, cloud migration, AI/ML, data science, and business intelligence initiatives. Leads collaborative teams in evaluating data, designing solutions, and managing operational data flows. Requires TS/SCI clearance with polygraph and experience in all-source analysis and data engineering.

Designs, builds, deploys, and maintains scalable cloud-native data platforms and pipelines using AWS. Supports cloud migration, data science, AI/ML, and business intelligence initiatives by organizing structured and unstructured data. Responsibilities include database architecture, data acquisition and preparation, software development, platform modernization, analytics architecture evaluation, and cross-functional team leadership. Requires TS/SCI clearance with polygraph and substantial all-source analysis experience.

Designs and develops cloud data architectures, ingestion frameworks, data models, and analytical platforms. Advises clients on cloud migration, data warehousing, technical approaches, and implementation roadmaps. Collaborates with stakeholders through requirements gathering, workshops, whiteboarding, and project meetings while deploying end-to-end cloud analytics solutions. Requires experience with cloud platforms, big data technologies, BI tools, data warehousing methodologies, programming, SQL, version control, and Agile/DevOps practices.

Gather client requirements and architect, develop, and deploy cloud data platforms, warehouses, ETL processes, pipelines, APIs, and BI solutions. Perform advanced SQL and data modeling, support deployments and integrations, diagnose technical issues, mentor staff, contribute to innovation and practice development, and assist with project management. The role requires approximately 20% overnight travel and primarily in-person work.

Own the technical direction, architecture, roadmap, and operational health of Teamfight Tactics’ data ecosystem. Build scalable batch and near-real-time data systems, telemetry, schemas, data models, governance, observability, and reliable sources of truth. Lead cross-functional initiatives, define engineering standards, optimize costs, mentor practitioners, and partner with game, product, insights, and data science teams across feature development and live operations.

Participates in a 12-month new-graduate development program while designing, building, deploying, and operating data architectures and pipelines. Develops processes for capturing, transforming, storing, and maintaining structured and unstructured data across distributed and local systems. Applies automation, big-data, artificial intelligence, and machine-learning techniques to support data integrity, compatibility, and evolving business requirements.

Own and expand Chicory’s analytical data platform supporting advertising, campaign, financial, product, and publisher reporting. Design BigQuery architecture, build batch and streaming pipelines with Python, SQL, Beam, Dataflow, and Airflow, and develop governed data marts and BI datasets. Establish data quality, observability, reconciliation, access controls, cost management, and engineering practices. Partner with engineering, finance, product, campaign management, sales, and leadership while leading incident recovery and documenting systems.

Support senior engineers in building, testing, and maintaining enterprise data pipelines and integrations. Write and optimize SQL queries, implement data quality checks, logging, and documentation, and participate in source control, code reviews, sprint activities, and support response. Complete and present an assigned data engineering project while developing practical skills in databases, scripting, ETL/ELT, and cloud data engineering.

Builds and maintains cloud-based data pipelines, transformations, semantic views, conformed dimensions, and analytical data models supporting reporting and AI/ML. Implements data quality checks, documentation, lineage, testing, release-readiness evidence, and defect resolution. Collaborates with data owners, governance, engineering, security, product, and customer teams to deliver reliable, governed data products. The role supports enterprise data modernization, migrations, DataOps, and production data platforms for a federal client.

Own production data ingestion pipelines for healthcare and benefits data, including normalization, mapping, validation, reconciliation, observability, and secure handling of sensitive information. Unify census data processes, scale the platform, improve identity matching, and build automation and TypeScript tooling. The role requires strong Python and SQL skills, production orchestration experience, reliable testing and data-quality practices, and effective communication with technical and nontechnical stakeholders.

Develops and supports enterprise reporting, dashboards, data pipelines, and analytics solutions using SSRS, Tableau, OBIEE, SQL, and related technologies. Translates business requirements into governed reporting products, optimizes queries and data integrations, validates results, resolves production issues, and maintains documentation. Collaborates with data engineering, governance, security, business, and data science teams across cloud, on-premises, and hybrid environments while supporting data quality, compliance, and self-service analytics.

Develop and maintain Databricks notebooks, workflows, GitLab repositories, and foundational CI integrations. Troubleshoot access controls and Python library issues, integrate Databricks, GitLab, Jira, and Confluence APIs, and analyze project activity data. Establish merge request and code review standards, support DevSecOps practices, evaluate new technical tools, and provide technical guidance to combatant commands and cross-functional engineering teams. The role is onsite at Andrews AFB three days weekly and remote two days.