Top Senior Data Engineer Jobs in Memphis, TN

Lead design and implementation of scalable, HIPAA-compliant data pipelines and platforms for healthcare ML. Build ETL, orchestration, and tooling for processing EHR, claims, pharmacy, and bioinformatics data; collaborate with data scientists to produce modeling-ready datasets and ensure data quality, reliability, and operational excellence.

As Lead Data Engineer, you will guide a team, manage the data platform, and oversee the development of ML infrastructure and feature stores.

The Senior Quantitative Data Engineer will build and maintain scalable data pipelines for quantitative investment research, ensuring data integrity and compliance, while collaborating with various teams for data architecture and product strategy.

The Data Engineer will develop and optimize data pipelines, manage data architecture, support cross-functional teams, and ensure data security and integrity.

The Data Engineer at Netflix builds systems for efficient data processing and modeling, collaborating with various teams to empower analytical insights and product features.

The Data Engineer will build scalable privacy-centric data frameworks, engineer data pipelines, and ensure compliance with privacy regulations at Netflix.

As a Staff Data Engineer, lead the technical roadmap for data infrastructure, manage complex data architectures, and mentor engineers while driving the organization's data platform innovations.

Lead and mentor a data engineering team to design and operate scalable ETL/ELT pipelines and Snowflake data warehouse solutions using Python, DBT, Matillion, and AI tools; establish standards, ensure data quality and governance, and collaborate with analytics, product, and BI stakeholders to deliver production-ready data platforms.

The Senior Data Engineer at Unchained will design and implement data pipelines, integrate APIs, ensure data governance, and mentor team members while focusing on accuracy and security.

The Principal Data Engineer will lead the Data Resolution team, focusing on complex data challenges using Spark, system architecture, and mentorship, to optimize graph data pipelines.

The Lead Data Consultant will design and deliver scalable data solutions, manage project teams, and optimize client data environments, ensuring effective project execution and communication.

Design, build, and scale data pipelines and integrations for the TDX platform. Implement REST API integrations, ingest and unify customer data, optimize pipelines for performance and quality, ensure data security and governance, and collaborate with Product, Data Science, and customer teams to deliver reliable analytics-ready data.

Design and maintain ELT pipelines, build dimensional (star/snowflake) analytics models, implement data transformations and quality checks, document data lineage and governance, partner with BI users, and mentor junior engineers to deliver performant analytics for business reporting and KPIs.

Design, build, and operationalize large-scale data platforms and pipelines on GCP. Mentor engineers, ensure data quality and system performance, and deploy production data solutions using BigQuery, Dataflow, Airflow, Terraform, and related tools.

Lead end-to-end enterprise data migrations and consolidations from legacy ERPs to cloud platforms. Design cloud architecture, build automated ETL/ELT pipelines and ontology-driven schemas, implement CDC and validation frameworks, deliver dashboards and migration controls, advise executives, and develop reusable accelerators while mentoring teams and enabling client post-migration governance.

The role involves building and optimizing data pipelines, modeling datasets, applying machine learning techniques, and supporting data strategies. Candidates should have experience with Python, data lakes, warehousing, and related technologies.

Design and deploy scalable data infrastructure and models, maintain CDC pipelines, build reporting tools and dashboards, write high-performance SQL, partner with product and engineering to enable enterprise-wide analytics and data-driven decision making.

The Data & Analytics Engineer will model and serve data, improve architecture, and collaborate with teams to sustain the data strategy, requiring 5+ years of experience.

The Senior Data Engineer will manage and transform data pipelines, implement changes in Snowflake, monitor costs, and resolve data issues.

Design, build, and operate scalable batch and streaming data pipelines; partner with customer and product teams to implement health system integrations; improve monitoring, tooling, and data accessibility; serve as a dataset and tooling subject matter expert.

Technical leader building scalable data pipelines, analytics infrastructure, and APIs. Own architecture, optimize large-scale query performance, mentor engineers, and partner with product and integration teams to deliver real-time and historical analytics.

Design, build, and operate cloud-native data platforms and scalable pipelines using Snowflake and dbt. Lead orchestration, CI/CD, observability, and performance tuning. Collaborate on backend services and limited frontend work, mentor engineers, define modeling standards, and participate in multi-team architecture and system design.

As a Senior Data Engineer, you'll design, build, and optimize data infrastructure while collaborating with teams to enhance data flow and integration across platforms.

The Senior Data Engineer will design and build data pipelines and infrastructure to support data science and business intelligence solutions, utilizing AWS services and streaming technologies.

Design and maintain high-quality data pipelines, develop DBT models, collaborate with analytics and data science teams, and optimize data operations for scalability.