Top Data Engineer Jobs in Tampa, FL

Develop custom connectors on Airbyte for data ingestion from various platforms, ensuring accurate data integration and transformation. Collaborate with stakeholders and perform testing for reliability.

The Snowflake Data Engineer and Product Owner will manage the Snowflake data analytics project, collaborating with stakeholders, leading Agile practices, and ensuring quality deliverables through effective team coordination and backlog management.

The Snowflake Data Engineer will work on data cleansing and harmonization, moving from legacy systems to SAP S4, focusing on ETL/ELT development and view creation.

This role involves designing, building, and maintaining data pipelines on Snowflake. Responsibilities include ensuring data quality and collaborating with stakeholders to deliver solutions.

The AWS Data Engineer will work on a data cleansing and harmonization project, focusing on AWS ETL design and development using various AWS services.

The Snowflake Data Engineer will design, build, and maintain data pipelines on Snowflake, optimizing performance and ensuring data quality while collaborating with stakeholders.

Design, build, and own end-to-end data systems and pipelines powering payments, fraud response, and reporting. Implement streaming and batch integrations, APIs, and workflow orchestration. Define data correctness with monitoring, alerting, and tests. Create reusable patterns and collaborate with stakeholders to clarify requirements and tradeoffs.

Design, build, and maintain scalable data pipelines, data models, ETL/ELT, and BI solutions. Collaborate with data scientists and stakeholders to improve data quality, accessibility, and PHI security. Develop and document workflows, optimize processing/storage, support data warehouse and visualization, and adopt AI tools to drive data-informed outcomes.

As a Data Engineer at Common Room, you'll build ETL pipelines, process billions of events daily, and collaborate on backend projects using AWS, Postgres, and Node.js.

Lead design, build, and optimization of Sezzle's large-scale data warehousing and pipelines. Own data infrastructure KPIs/SLAs, improve Redshift performance, evolve the data stack, implement ETL/ELT workflows, and partner with cross-functional teams to deliver reliable, scalable datasets.

Design and maintain data systems for business-critical insights, connect data across platforms, build ETLs, and support business data decisions.

The Principal Data Platform Engineer leads the architecture and development of the enterprise data platform, focusing on analytics, data science, and AI/ML capabilities. They establish standards for data quality and observability, design data ingestion and processing patterns, and mentor team members to enhance technical capabilities.

As a Senior Data & Analytics Engineer, you'll lead data initiatives, manage a team, and ensure data quality while turning insights into actionable decisions across the company.

As a Senior Data Engineer, you will design and maintain scalable data pipelines, focusing on architecture, ingestion, storage, and analytics on GCP. You'll collaborate with stakeholders and optimize data structures for performance while ensuring adherence to data governance and compliance standards.

The Sr. Data Engineer will architect and build an end-to-end data platform, developing data pipelines and infrastructure for AI and robotics teams, ensuring data integrity and governance, and collaborating on ML model development.

The Senior Data Analytics Engineer will develop data pipelines, support data-driven decision-making, collaborate with stakeholders, and improve data quality and processes.

The Data Engineer builds and maintains data infrastructure, develops data pipelines, ensures data quality, and collaborates with teams for insights.

As a Staff Software Engineer in Data Engineering, you will design, build, and optimize robust data systems to ensure data quality, performance, and stability, while mentoring team members and collaborating with cross-functional teams.

Lead Data Engineer responsible for defining architecture, engineering standards, and best practices for the enterprise data platform, collaborating with distributed teams for modernization and scalability.

Design and scale data infrastructure, ensure data quality and governance, collaborate with teams on data products, and modernize practices.

The Senior Data Engineer will scale and evolve the data platform, develop ETL/ELT pipelines, establish best practices, and optimize systems for performance while collaborating with various teams.

The Sr. Data Engineer will build automation and observability for the EDAS platform, focusing on reliability through data-driven tools and workflows. Responsibilities include developing frameworks for monitoring, optimizing data pipelines, and collaborating to enhance platform performance and compliance.

Design and maintain data processing pipelines for geospatial data using ArcGIS. Ensure data quality, compliance with standards, and collaborate with teams for scalable solutions.

Lead design, build, and support of cloud-based ETL, data warehousing, and reporting solutions. Develop/optimize ETL pipelines, data models, and queries; deploy containerized services on Kubernetes; automate workflows; mentor teammates; collaborate with architects, data scientists, and stakeholders to deliver scalable analytics and reporting products.

The Senior Data Engineer will design and implement data processing pipelines using Java and Spark, optimize performance, and mentor junior engineers while ensuring compliance with data governance standards.