Top Senior Data Engineer Jobs in Tampa, FL

Design, deploy, and maintain scalable data infrastructure and orchestration for analytics and ML; write optimized SQL over large warehouses; partner with engineering and product to structure source systems; maintain CDC pipelines; scale reporting and expose analytical datasets enterprise-wide while ensuring data management, security, and compliance.

Design and own end-to-end data platform architecture, build ingestion and transformation pipelines, model multi-tenant datasets, optimize Postgres and ClickHouse performance/cost, implement orchestration and observability, define data quality and reconciliation standards, and mentor data/product engineers.

Design, implement, and manage scalable multi-cloud data platforms and ELT pipelines (AWS/Azure). Build and optimize Snowflake data models, dbt transformations, and Airflow orchestration. Define data engineering standards, enforce governance and quality, collaborate cross-functionally, and mentor global/offshore teams.

Build and maintain automated ETL/ELT data pipelines, improve data quality and monitoring, optimize Postgres and BigQuery schemas and queries, develop internal tooling, support data governance (HIPAA), participate in on-call rotation, and collaborate across engineering teams to scale data systems.

The Data Engineer will design and maintain data pipelines, enhance the data warehouse, support machine learning applications, and collaborate with various teams to leverage data effectively.

The Senior Data Engineer will build and maintain ETL/ELT pipelines, optimize SQL queries, and collaborate on machine learning workflows, driving data engineering best practices.

As a Sr. Data Engineer at Lyra Health, you will build and scale core data infrastructure, design data warehouses, and create efficient data pipelines while collaborating across departments.

The Senior Data Engineer will design and maintain data pipelines, write production-grade Python and SQL code, and support AI initiatives while collaborating across teams.

The Data Architect/Data Governance Lead supports the Medicaid Enterprise Data Warehouse by leading data architecture, metadata management, and governance processes, ensuring compliance and scalability.

In this role, you will design data architecture, lead integration strategies, mentor engineers, and drive AI infrastructure for cross-division data systems.

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.

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.

Design, build, and automate scalable batch and streaming data pipelines, implement data models and ETL, automate deployments, support ML/experimentation, maintain server architecture, and partner with stakeholders to deliver analytics and data-driven tools.

Own and architect the semantic layer and metrics/metadata for the data platform (Databricks/GCP). Build AI-ready models, enforce modeling and documentation standards, implement observability/testing for pipelines, enable self-serve analytics, and collaborate across product, clinical, and business teams to translate questions into reliable data solutions.

Design, operate, and scale end-to-end data infrastructure and pipelines. Build reusable data models and a semantic layer, ensure data quality and privacy, implement observability and SLAs, support marketing and growth feeds, partner with cross-functional stakeholders, and enable ML/AI consumption and reverse ETL workflows.

Design, build, and maintain scalable, secure data architectures, models, and ETL pipelines. Integrate diverse data sources, optimize performance and data quality, implement governance, monitor production SLAs, and collaborate with data scientists, analysts, and product teams. Provide technical leadership, documentation, and training to improve engineering practices across the organization.

Lead a team of 5-6 data engineers to design and implement scalable data pipelines (Airflow), manage Snowflake data architecture, build real-time streaming solutions with Kafka/Spark Streaming, develop and integrate APIs, enforce code quality, and drive technical decisions and best practices.

Design, build, and maintain scalable ETL/ELT pipelines and product-level data architectures. Improve pipeline performance and data freshness, lead code/design reviews, mentor engineers, and collaborate with Data Science, Product, and Engineering to make data reliable and accessible.

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.

The Senior Data Engineer will design and implement lakehouse architectures, optimize ClickHouse deployments, develop ETL/ELT pipelines, and create data models to support analytical and operational functions.

Own and evolve end-to-end data pipeline architecture across ingestion, transformation, modeling, and serving. Lead platform improvements (cost, compute efficiency, access control), CI/CD, monitoring, and incident response. Drive cross-team technical initiatives, mentor engineers, and integrate AI tooling to improve workflows while remaining hands-on building and debugging production pipelines.

Own end-to-end data pipelines (ingest, dbt transformations, BigQuery warehousing) and consolidate the analytics stack into a single source of truth. Build and maintain dbt models with tests and documentation, establish data quality and observability, own product analytics and instrumentation, partner with GTM and marketing on reporting, and prepare for high-volume/streaming ingestion.

Lead design, build, test, and maintain scalable cloud data platforms and pipelines (ETL/ELT, batch and streaming). Ensure data quality, governance, security, CI/CD deployment, performance tuning, migration/archival, and mentor data engineering teams to support analytics and AI/ML use cases for a federal modernization program.

Design, build, and maintain production-scale data systems and web-scale datasets (Spark/Flink) to support personalization ML. Drive dataset/schema design, collaborate with algorithm teams, and improve distributed big-data processing for member experience.

Design, build, test, deploy, and support enterprise data solutions for financial reporting, reserving, and claims. Develop and maintain pipelines, transformations, data models, and controls using SQL, Python, PySpark, and Microsoft Fabric. Automate reconciliations and data quality checks, partner with business stakeholders, perform testing, review code, mentor peers, and resolve production issues to improve reporting accuracy and operational efficiency.