Über
Lead Data Engineer / Data Architect
Location:
Tampa, FL or Cary, NC
Work Type:
Hybrid (3 days onsite)
Position Overview We are seeking a Lead Data Engineer / Data Architect to play a critical role in designing and delivering enterprise‑scale data and analytics solutions. This position sits within a centralized Data & Analytics organization supporting enterprise‑wide data initiatives and will be responsible for architecting modern data platforms that enable scalable, high‑performance analytics and business insights.
This role combines hands‑on data engineering expertise with architectural leadership, driving the design of data hubs, pipelines, and cloud‑based data platforms. You will partner closely with business, analytics, and technology teams to build next‑generation data solutions that support real‑time and batch analytics use cases.
Key Responsibilities
Design and implement end‑to‑end data architecture from source systems to analytics, reporting, and application consumption
Build and maintain scalable ETL/ELT pipelines to ingest and process large volumes of structured and unstructured data
Develop high‑performance, reliable, and maintainable data pipelines using modern cloud and big data technologies
Design and implement data lakes, data warehouses, and data products for enterprise analytics
Create reusable frameworks and components to improve efficiency, scalability, and cost optimization
Optimize Spark jobs and data pipelines for performance and cost in large‑scale environments
Leverage cloud platforms (preferably Azure) to deliver PaaS‑based enterprise data solutions
Implement solutions that support dynamic scaling, high‑volume workloads, and real‑time processing
Establish and promote modern engineering practices including CI/CD, automated testing, and code quality standards
Develop and manage API‑based data services and data catalogs
Collaborate with global teams, business analysts, and stakeholders to gather requirements and deliver scalable solutions
Provide recommendations for performance tuning, architecture improvements, and optimization
Required Qualifications
8+ years of overall experience with 6+ years in data engineering and big data development
Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field
Strong expertise in data architecture (traditional and modern cloud‑based patterns)
Hands‑on experience designing and building data lakes, data warehouses, and analytics platforms
Extensive experience with Spark (Scala/Python) and performance tuning
Strong experience with cloud data platforms (Azure preferred, AWS acceptable)
Experience building data ingestion, transformation, and curation pipelines using tools such as:
Azure Data Factory
Databricks
Delta Lake
Cosmos DB
Proficiency in Python and/or Scala for data engineering
Experience working with unstructured and large‑scale datasets
Strong understanding of data modeling, data integration, and architecture patterns
Experience with CI/CD and version control (e.g., Azure DevOps)
Strong problem‑solving skills and excellent communication abilities
Preferred Qualifications
Experience with Azure Event Hub for streaming/data integration
Experience with Azure Synapse (SQL Pools) performance tuning
Knowledge of Cosmos DB and API optimization
Experience with Hive and large‑scale data partitioning strategies
Scripting experience with Bash, Shell, or PowerShell
Experience working with Azure DevOps pipelines
Exposure to AI/ML‑driven data workflows or automation use cases
What Makes This Opportunity Unique
Opportunity to lead architecture for enterprise‑scale data platforms
High‑impact role driving modern cloud and big data transformation initiatives
Work across global teams and complex data ecosystems
Blend of hands‑on engineering and strategic architecture leadership
Exposure to cutting‑edge technologies in cloud, big data, and AI‑driven data solutions
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Sprachkenntnisse
- English
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