Top Senior Data Engineer Jobs in Orlando, FL

The Senior Data Engineer handles ChowNow's data platform, collaborating with teams to enhance data availability and insights, supporting internal and customer-facing products.

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 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.

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 Data Engineer will design, build, and maintain analytics-ready Data Marts, create resilient data pipelines, and ensure data integrity, working closely with analytics teams to deliver reliable datasets.

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 Data Engineer will design and maintain data models on Snowflake, enforce data standards, manage security, optimize SQL, implement CI/CD, and mentor junior staff.

Lead design, build, and optimization of a Snowflake-centric cloud data platform and dbt transformation layers. Develop reliable pipelines from sources like Salesforce, ensure data quality, performance tuning, and compliance with PHI/PII/HIPAA. Collaborate with analytics, product, and engineering teams to deliver scalable, documented, analytics-ready datasets and platform standards.

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.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

Design, build, and optimize distributed query solutions using Starburst/Trino. Enable secure, governed data access across cloud and on-premises sources, implement data federation and query optimization, support IAM and governance in a federal environment, develop backend services and CI/CD, and troubleshoot performance in cloud-native systems.

Design, implement, optimize, and maintain scalable, high-availability database solutions for a SaaS healthcare product. Integrate client data, resolve complex data issues, refactor systems for Azure, optimize MSSQL performance, participate in code reviews, and deliver features within Agile/Scrum to ensure reliable, high-performance data services.

Lead design and delivery of enterprise data centralization and automation for reporting and BI. Build and maintain ETL/SSIS pipelines, data orchestration, file delivery and quality controls, follow SDLC/agile, mentor junior engineers, and partner with business stakeholders to capture requirements and ensure timely data delivery.

The Lead Data Engineer will manage data engineering efforts, build scalable pipelines, ensure data integrity, and collaborate with BI and Analytics teams to support business growth.

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

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.

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.

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.

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

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

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.

As a Senior Data Engineer, you will enhance the data lakehouse, optimize data workloads, perform complex transformations, and develop frameworks to improve delivery velocity, focusing on cybersecurity solutions.

The Senior Data Engineer will design and build scalable data pipelines and models, ensuring data quality and optimizing data infrastructure using AWS and Snowflake. Responsibilities include leading projects, integrating APIs, and collaborating across teams to enhance data products for value-based care.

Lead the design of DataOps platforms, focusing on scalable data infrastructures and automation frameworks. Oversee robust data orchestration and establish quality frameworks.