Top Data Engineer Jobs in Tampa, FL

Lead and manage client accounts and teams to build modern data ecosystems, convert insights into strategic opportunities, and deliver managed data and analytics programs. Oversee project planning, budgeting, execution, quality, risk management, and mentoring of junior staff while promoting cloud-scale development and rigorous professional standards.

Design and implement data architecture and scalable ETL/ELT pipelines in cloud environments. Analyze complex data problems, mentor junior staff, ensure data governance and security compliance, collaborate with stakeholders, and build client relationships while developing technical expertise and personal brand.

Design and implement scalable data solutions and manage advanced data ecosystems. Analyze complex problems, build ETL/ELT pipelines and data warehousing solutions, maintain data governance, mentor junior staff, and build client relationships to deliver high-quality managed data and analytics services.

Design and build data infrastructure, pipelines, and ETL solutions using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality, collaborate with clients, and implement security and data modeling best practices to enable analytics and business insights.

Lead design and delivery of data architecture, build and maintain ETL/ELT pipelines, manage data warehouses and lakes, enforce governance and security, mentor team members, liaise with stakeholders, and optimize cloud-based data solutions for performance, cost, and scalability.

Support client engagements by building and maintaining ETL data pipelines and BI solutions; perform SQL optimization, data architecture and modeling; develop reports and dashboards using Oracle BI, QlikView, and Spotfire; apply analytics to generate strategic insights and improve data quality in regulated environments.

Lead design and implementation of data architecture, build data pipelines/integration and transformations, document data models and flows, ensure governance and security compliance, advise clients strategically, drive large projects, and mentor/coaching teams to deliver high-quality data solutions.

The Data Engineer will build and maintain data pipelines, optimize workflows, manage infrastructure, and enhance pipeline observability while collaborating with teams for effective data delivery.

Design and implement data architecture and scalable ETL/ELT pipelines using cloud platforms (AWS/Azure/GCP). Develop data models, ensure governance and security compliance, analyze complex problems, mentor junior staff, build client relationships, and enhance technical skills to deliver high-quality data solutions.

Design and build data infrastructure, pipelines, and integration solutions using cloud and big-data tools. Develop and manage data lakes and warehouses, apply data architecture and dimensional modeling, validate data quality, implement security best practices, and collaborate with clients to deliver analytics and data strategies. Mentor peers and manage growing client responsibilities as a Senior Associate.

Lead design and delivery of cloud-based data architecture, data models, ETL/ELT pipelines, data warehouses/lakes, and data security. Manage projects, mentor team members, ensure governance compliance, collaborate with stakeholders, and optimize cloud infrastructure for performance, cost, and scalability.

Lead design and implementation of data architecture and cloud-based data engineering solutions. Manage large projects, translate stakeholder requirements into technical designs, ensure data governance and security, develop data models and pipelines, advise clients strategically, and coach teams to deliver operational excellence.

The Data Engineer will develop and implement ETL processes, design data architectures, work with data platforms, and ensure data solutions meet scalability and security needs. Responsibilities include mentoring junior engineers and collaborating with stakeholders to gather requirements and optimize data transformations.

Build, model, and maintain scalable BigQuery-based data solutions on GCP. Implement performant data models, storage partitioning/clustering, ETL improvements, data validation, and documentation. Collaborate with architects, data scientists, and engineers to deliver governed, high-quality data for reporting and AI initiatives.

As a Data Engineer, you'll lead data engineering projects, develop data transformations, build workflows with Apache Airflow, and ensure data quality and integrity while collaborating with stakeholders.

Lead data engineering engagements within Technology Consulting: design data architectures, build and maintain ETL pipelines, implement BI solutions, coach teams, engage stakeholders, validate client outcomes, and drive solution optimization and performance tuning.

Lead data engineering projects and teams to build scalable ETL/ELT pipelines, data architectures, and cloud analytics solutions. Use tools like DataStage, AWS (S3, Glue, Redshift), DB2, SQL Server, GoldenGate, and BI tools to deliver reporting, performance tuning, and client-facing insights while mentoring staff and ensuring project delivery and quality standards.

Lead development and execution of a unified software quality data strategy for Electronic Systems. Build automated ETL pipelines, real-time dashboards, alerts, and analytics; coordinate across engineering teams and sites; deliver data-driven insights to leadership; and enable continuous improvement of software quality in regulated, embedded aerospace environments.

Lead technical strategy, architecture, and modernization of enterprise master data and data lakehouse platforms. Design and implement large-scale data pipelines, databases, and distributed systems using Python, Spark, Redshift, Iceberg and AWS services. Ensure performance, reliability, governance, CI/CD, and AI-enabled engineering practices while mentoring senior engineers and aligning cross-functional stakeholders.

As a Senior Data Engineer at Jellyfish, you'll build and maintain data pipelines, optimize orchestration, automate CI/CD processes, and enhance data integration while ensuring high performance and reliability.

Lead design and operation of large-scale data pipelines and data APIs. Build Spark/PySpark workflows on Databricks, optimize job performance, manage data quality and observability, and develop MCP servers and AI-agent integrations. Mentor engineers, define standards, support production incidents and on-call rotations, and collaborate with stakeholders to deliver scalable data platform products.

Lead architecture and buildout of a new graph-backed enterprise data platform: design ingestion, graph and relational storage, entity resolution pipelines, temporal models, ETL/ELT pipelines, governance, APIs, and production connectors. Ship scalable graph data models, traversal queries, and platform roadmap while enabling observability, security, and containerized deployments.

Build and maintain scalable, governed data pipelines from ingestion through transformation and integration. Implement schema validation, data quality checks, job monitoring, and production-grade APIs. Work with Python, SQL, Airflow, dbt, AWS (EMR, Athena, S3), Iceberg/Parquet, and contribute to CI/CD, observability, and on-call support while collaborating with analytics and product teams.

Lead architecture and reliability of the data platform, build and harden ingestion (batch and CDC), own BigQuery+dbt transformations, establish testing/observability/governance, mentor engineers, develop Python tooling and APIs, run POCs for lakehouse/open table formats, and define AI-assisted development practices.

Design, build, and operate large-scale data platforms and Spark/PySpark pipelines. Enable data integration, modeling, quality, and observability. Build MCP servers and AI-augmented tooling, mentor engineers, and lead cross-functional projects to deliver reliable data products.