Top Data Engineer Jobs in Nashville, TN

Design, build, and maintain scalable ETL/ELT pipelines ingesting travel-related data from multiple sources. Integrate and model data in cloud warehouses (Snowflake/BigQuery/Redshift), implement data quality and monitoring, support real-time streaming, and ensure data governance and regulatory compliance. Collaborate with analysts, data scientists, and product teams to deliver reliable datasets for personalization, forecasting, and optimization.

Build and maintain scalable cloud data pipelines and governance to support analytics across claims, EHR, and real-time patient data. Deploy and operate Snowflake/dbt/AWS-based infrastructure, enable real-time analytics, partner with clinical, product, and engineering teams, and deliver insights that inform care delivery, payer collaboration, and business decisions.

The Data Engineer will build and maintain scalable data pipelines, improve ETL processes, collaborate with AI/ML teams, and contribute to engineering culture.

The Data Engineer at Anteriad will design, build, and optimize data pipelines, manage data integration processes, support analytics efforts, and collaborate with stakeholders to deliver scalable data solutions.

Build and operate scalable Databricks Lakehouse data platforms, including Bronze/Silver/Gold pipelines, feature tables, batch and streaming ingestion, data quality controls, modeling, performance optimization, governance, and production support. Partner with data science, AI, and platform engineering teams to deliver trusted healthcare and member data products for machine learning and decision intelligence workloads.

Lead the architecture, delivery, governance, quality, and reliability of Databricks Lakehouse data products. Build scalable batch and streaming pipelines, feature layers, and real-time data architectures supporting machine learning and decision intelligence. Optimize Spark and Delta Lake workloads, enforce PHI/HIPAA compliance, and establish observability and data quality standards. Lead a small engineering team while remaining hands-on, partnering with data science, AI, platform, and backend teams on microservices, databases, rules engines, APIs, testing, and resilient production systems.

As a Data Engineer, you will build and optimize data pipelines, ensuring accurate data delivery that informs pricing and market analytics at Alt.

Build and maintain data pipelines, applications, workflows, and governance in Palantir Foundry. Apply industrial engineering and operations research methods to analyze depot/MRO capacity, throughput, and bottlenecks, integrate ERP/MRO data into simulation models, deliver decision-support briefings, and support platform monitoring, automations, and client engagement.

Lead data engineering work across migrations, pipelines, integrations, and APIs. Design, build, deploy, test, monitor, and support production data solutions while ensuring data quality, validation, and adherence to architectural standards in an agile continuous-delivery environment.

Design, build, and operate scalable PostgreSQL databases and cloud-native data infrastructure. Build and maintain ETL/ELT pipelines, optimize query and server performance, ensure high availability and disaster recovery, improve observability, troubleshoot production issues, guide schema and application design, evaluate database technologies, and mentor junior engineers to support reliable, secure data-driven applications.

Lead pre-sales data engineering engagements to design and implement scalable lakehouse data platforms (Snowflake/Databricks). Advise customers on data strategy, governance, pipelines, AI-ready foundations, migrations, and translate technical solutions into business outcomes while supporting sales and partner enablement.

Design, build, and maintain ingestion and transformation pipelines for a knowledge-graph analytics platform. Profile and prepare structured and semi-structured source data, ensure data lineage and traceability, implement transformation logic for graph loading, collaborate with data scientists on graph modeling and entity resolution, improve pipeline reliability, and document ingestion patterns using version control and issue tracking.

The Data Engineer will design and implement data architecture, develop data ingestion pipelines, collaborate with stakeholders, and improve data-related processes.

Design, build, and maintain AWS-based data pipelines and ETL processes using Glue, Spark/PySpark and EMR. Integrate multiple data sources into data lakes and Redshift, implement DevOps CI/CD practices, and work with Kafka, Hudi, and various AWS storage and analytics services.

The job involves leveraging AWS and Snowflake for data engineering tasks within a technology-focused company, requiring US residency.

Design and build a medallion architecture using dbt and Microsoft Fabric, create and maintain data ingestion pipelines, and implement governance, lineage, documentation, and quality checks to support self-serve analytics while collaborating with cross-functional teams.

Own and optimize data infrastructure and ETL/ELT pipelines using SSIS and Microsoft Fabric. Build and maintain SQL Server data warehouse staging, transformations, and lakehouse ingestion. Implement CI/CD, version control with GitHub, monitor pipeline health, troubleshoot data issues, document data flows, and translate stakeholder requirements into data engineering solutions that support BI reporting.

The Data Engineer will design and maintain data pipelines, optimize cloud data warehouses, and collaborate with analytics teams while mentoring junior staff.

Designs and implements scalable data and technology solutions, develops ETL pipelines and APIs, manages cloud and big-data platforms, maintains data models, supports monitoring and scheduling, participates in Agile development and technical reviews, and mentors junior engineers.

Seeking a Senior BODS Developer to develop and maintain complex BODS processes for data transformation. The role includes improving data quality using Information Steward and GAC/URAC techniques, collaborating with teams, creating documentation, and mentoring others.

Design, build, and maintain scalable data pipelines and tenant-aware APIs to ingest and transform data from varied sources. Work with event-driven and batch architectures, implement authentication and integration patterns, ensure observability/monitoring, optimize data flows for cost and performance, and collaborate with product, infrastructure, and engineering teams to onboard and maintain data sources at scale.

The Senior Data Engineer will design and implement complex data models, collaborate on data governance, lead data initiatives, and mentor team members.

Responsible for designing, developing, and maintaining scalable data pipelines and infrastructure, implementing data governance, and collaborating with teams to meet data needs.

Build and maintain production-grade data pipelines and ELT processes using Python, SQL, Airflow, and dbt within AWS. Design optimized schemas in PostgreSQL and Redshift, leverage AI/LLMs to improve development, automation, testing, and data quality, and scale infrastructure for large healthcare datasets.

Build and manage data pipelines, ETL workflows, and DAGs using dbt, Apache Airflow, Python, SQL, and Snowflake. Develop custom Airflow operators and hooks, perform data modeling and source-to-target mapping, and implement data quality and cleansing processes. Use cloud platforms, CI/CD, version control, and Snowflake utilities including Snowpipe, Tasks, Streams, stored procedures, and data sharing. Collaborate across teams, communicate insights, solve complex problems, and participate in on-call escalation.