Top Data Engineer Jobs in Miami, FL

Lead and manage teams delivering modern data ecosystems and managed data & analytics programs. Oversee project planning, budgeting, delivery, quality, risk management, and stakeholder engagement while mentoring staff and converting data insights into strategic opportunities.

Design and implement data architecture and scalable ETL/ELT pipelines using cloud platforms (AWS, Azure, GCP). Analyze complex problems, mentor junior team members, ensure data governance and security compliance, build client relationships, and develop technical and business domain expertise.

Design and implement scalable data solutions and advanced data ecosystems, build ETL/ELT pipelines and data warehouses, analyze complex problems, mentor junior staff, maintain delivery standards, and cultivate client relationships while supporting data governance and analytics initiatives.

Design and build data infrastructure, pipelines, and transformations using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality, implement security, and collaborate with clients to deliver actionable insights and data strategies.

Lead design and delivery of cloud-based data architecture, data models, ETL/ELT pipelines, and data warehouse/lake solutions. Manage teams, ensure data governance and security, mentor staff, troubleshoot pipelines, and collaborate with stakeholders to translate business requirements into technical solutions.

Design, build, and maintain data pipelines and ETL processes; optimize SQL and data architectures; create BI reports and dashboards using Oracle BI, QlikView, and Spotfire; analyze data to generate strategic insights for clients; improve data quality and support client engagements in regulated environments.

Lead design and implementation of data architecture, build data pipelines and integrations, manage large projects, ensure governance and security compliance, translate stakeholder requirements into technical solutions, and coach and grow diverse teams while advising clients strategically.

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 efforts within Technology Consulting: design data architectures and pipelines, implement AWS/Redshift solutions, manage ETL (DataStage), deliver BI (SQL Server, DB2, QlikView, Oracle BI), coach teams, engage stakeholders, and validate outcomes to optimize client performance under managed services SLAs.

Lead and manage data engineering projects to build scalable ETL/ELT pipelines, data architectures, and cloud-based analytics (AWS/Redshift/S3/Glue). Mentor teams, collaborate with stakeholders, deploy BI and visualization solutions, and ensure project delivery, performance tuning, and client satisfaction.

The Senior Research Engineer will curate large datasets, automate data pipelines, optimize queries, and support data-driven research impacting business outcomes.

Lead design and implementation of scalable cloud data lakes, warehouses, and marts. Build ELT/ETL pipelines, apply Data Vault 2.0 and dimensional modeling, implement data quality, lineage, observability, and governance. Optimize Snowflake/Databricks/Synapse platforms, champion CI/CD and DataOps, mentor engineers, and enable AI/ML-ready data products through collaboration with architecture and product teams.

Lead design and delivery of scalable, secure cloud data pipelines and products. Translate requirements into architecture, apply advanced data modeling (Data Vault 2.0/dimensional), embed data quality, observability, security, and DataOps/CI-CD practices, optimize performance and cost, mentor engineers, and enable AI/ML-ready datasets within an agile DevSecOps model.

Design, build, and operate scalable cloud data pipelines and platforms (Azure preferred). Implement DevSecOps, CI/CD, automated testing, monitoring, performance tuning, and production readiness. Mentor engineers, drive operational excellence, and translate requirements into robust technical designs. Apply healthcare domain knowledge and collaborate in agile teams to deliver secure, reliable data products.

Design, build, and maintain scalable ETL/ELT data pipelines and data warehouses using Databricks, Spark, SQL Server, SSIS, and PL/SQL. Integrate healthcare data, optimize queries and performance, monitor data quality, support HIPAA compliance and data governance, and collaborate with stakeholders to deliver analytics-ready data assets.

Design, build, and automate scalable data platforms (lakehouses/warehouses). Implement and optimize ETL/ELT pipelines using Databricks and dbt, apply Medallion Architecture, manage IaC/CI-CD, ensure data security and governance, and integrate pipelines with BI tools while engaging with stakeholders.

Design, build, and maintain scalable data pipelines and analytical infrastructure using AWS and modern data stack (Snowflake, dbt). Collaborate with product, engineering, BI, and data science teams to automate reporting, optimize storage and performance, implement ETL/ELT processes, ensure data security, and support BI platforms and CI/CD deployments.

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.