Top Data Engineer Jobs

The Sr. Data Engineer - Databricks designs and maintains scalable data solutions using Apache Spark and Databricks, ensuring data quality and performance for analytics and reporting.

Lead migration to a Databricks lakehouse, design and maintain dbt medallion pipelines, improve ingestion and reliability, implement data quality and governance, build curated datasets, mentor engineers, and drive platform standards and documentation.

Design, implement, and maintain data interactions and backend systems using Python and Apache Spark. Build APIs, optimize ETL and distributed data processes, contribute to UI and automated testing, and support CI/CD-driven deployments within an agile team focused on healthcare quality reporting.

Support and monitor data pipelines and curated datasets, perform exploratory analysis and model validation, develop SQL data models in Snowflake, troubleshoot ETL/ELT jobs, integrate proprietary and third-party data, validate AI-generated insights, and collaborate with stakeholders to deliver Customer 360 and leadership analytics.

Design, build, and maintain scalable data pipelines, ETL processes, and automation tools (Python, SQL, Power Apps). Partner with stakeholders on technical designs, develop Streamlit front-ends on AWS, integrate systems (SQL Server, Active Directory), and recommend process improvements and emerging technologies to enhance internal audit automation and insights.

Lead design, build, and operate scalable AWS-based data pipelines and real-time ingestion for analytics and ML. Implement data modeling, automated validation, observability, and event-driven architectures; mentor engineers and collaborate with Product and ML teams to productionize feature stores and ML-ready datasets.

Design, deploy, and maintain global data platform infrastructure with emphasis on multi-region Databricks orchestration. Lead system architecture, optimize Databricks (Delta, Spark, Unity Catalog), implement IaC with Terraform, build CI/CD pipelines, troubleshoot platform issues, and collaborate with cross-functional teams to meet technical, governance, and performance requirements.

Design, build, and maintain scalable ETL/ELT pipelines, integrations, and data warehouses (Snowflake, MySQL, SQL Server). Implement workflow orchestration (Airflow), data quality, security, and CI/CD. Partner with analysts and tech teams, troubleshoot systems, and provide technical leadership and mentorship to shape long-term data strategy.

Design, build, and maintain scalable cloud and hybrid data platforms, ETL/ELT pipelines, and data models. Implement CI/CD and DevOps practices, ensure data quality, security, and governance, optimize production pipelines, lead modernization and integration efforts, and mentor junior engineers.

Design, operate, and optimize a secure, scalable Snowflake data platform for Workforce Analytics. Enable governed, least-privilege access for users, applications, and AI tools. Own Posit (RStudio) platform connectivity and usability. Partner on transformation pipelines (Coalesce), CI/CD, data quality, and platform governance to support analysts and data scientists.

Lead and deliver enterprise data programs: design Snowflake-based data solutions, data models, ETL and warehouse applications, provide architecture direction, drive technology transformation, collaborate with stakeholders, and apply advanced analytics (ML/AI/GenAI).

Develop and validate daily data feeds, reports, and applications; vet other developers' work for data integrity; collaborate with business partners; participate in Agile ceremonies; identify and improve ETL performance; maintain clear documentation.

Build and maintain dbt models and ETL/ELT pipelines on BigQuery and Daasity, connect marketing, inventory, and finance data, support KPI tracking and predictive models, deploy dashboards, and collaborate with AI and business teams to ensure clean warehouse outputs for analytics and automation.

Lead design and implementation of data architecture, ETL/ELT pipelines, and data models. Build dashboards (Power BI/Tableau), define performance metrics, ensure data quality and lineage, automate reporting, mentor junior analysts, present findings to stakeholders, and document processes. Onsite support in Frederick, MD with required business-hours availability.

Lead design and delivery of an enterprise Azure/SAP-based data and AI platform using Microsoft Fabric and SAP BDC. Define architecture, governance, IaC, CI/CD, reusable ingestion/integration patterns (including PI historian and SAP), semantic models, and partner with stakeholders to produce secure, scalable, production-grade analytics, reporting, and AI capabilities.

Design and implement scalable, production-quality data solutions using cloud-based big data technologies. Develop and optimize Spark/Hive workflows, write code in Scala/Python/Java, perform performance tuning, participate in SDLC and agile processes, and collaborate to identify and execute improvements.

Design, build, and maintain scalable analytics pipelines and data models. Write efficient SQL, create dashboards and reports, monitor data quality, and partner with cross-functional teams. Leverage AI tools to accelerate analytics workflows and improve decision-making across the company.

Design, build, and optimize scalable cloud-based data pipelines and infrastructure. Implement orchestration, real-time streaming, API integrations, data modeling, governance, and CI/CD; collaborate with cross-functional teams to ensure data quality and availability.

Implement Redpoint Customer Engagement Hub and RPDM ETL, data hygiene, and identity resolution. Build data ingestion/automation, troubleshoot client implementations, collaborate with development and project teams, and support product feature identification.

Lead design and evolution of Archer's data warehouse/lakehouse architecture, define modeling and governance standards, partner with stakeholders to build reusable data models, optimize storage and compute, and maintain production-grade, reliable ETL pipelines.

Build and scale ad-tech data infrastructure and pipelines ingesting SSP/DSP/GAM sources, transform log-level and CRM data into analytics-ready datasets, maintain warehouses, implement data quality and privacy controls, and support BI and analytics teams for real-time campaign insights.

Design, build, and maintain end-to-end batch and streaming data pipelines on GCP. Migrate legacy warehouses to BigQuery/Bigtable/ClickHouse, orchestrate workflows in Airflow, ensure data quality and observability, and partner with ML engineers on feature pipelines, drift monitoring, and retraining.

Lead design and implementation of scalable GCP-based data pipelines and semantic layers for enterprise healthcare analytics. Drive ingestion automation, BigQuery optimization, ETL/ELT orchestration, observability, data quality, and metadata management. Provide technical leadership, mentor engineers, and collaborate with architects and stakeholders to deliver production-ready cloud data solutions.

Design, develop, and implement Microsoft Azure Databricks data platforms and pipelines to ingest, cleanse, transform, and publish data. Assemble large datasets, collaborate with architects and leads to ensure fit-for-use data, apply coding standards, and drive process improvements.

Design, build, and maintain scalable cloud and hybrid data platforms, ETL/ELT pipelines, and data models. Implement CI/CD and DevOps practices, ensure data quality, security, and governance, optimize production pipelines, mentor junior engineers, and support data modernization and migration efforts for analytics and operational workloads.