Data Engineer Lead Data Warehouse Architect

Data Engineer Lead/Data Warehouse Architect (Level 3): Data Engineering Lead excels in data modeling, Lakehouse and Medallion Architecture concepts, and data/ML products delivery using an agile DevOps framework with a mastery of distributed data architectures essential for data, analytical and operational ML applications with demonstrated proficiency in frameworks including Spark, Kafka, Kubernetes, SageMaker, DBT, Juniper Notebooks, Docker, SQL, and visualization tools such as Power BI/Tableau with the following track record:

Roles and Responsibilities: Data Engineering Lead excels in data modeling, Lakehouse, and ML products delivery using an Agile DevOps framework with a mastery of distributed data architectures essential for data, analytical and operational ML applications with demonstrated proficiency in frameworks including DataBricks, Sagemaker, Spark, Kafka, Kubernetes, SQL, NoSQL DBs, Graph DBs, and visualization tools such as Power BI/Tableau.

The Data Engineer Lead serves as the primary State of Michigan technology lead engaging with the UoM proof of concept team to support best practice adoption within the state hosting environment and provides training to DAV data engineers. This role's responsibilities include: Oversee the design, development, and maintenance of data pipelines that move, transform, and prepare data for analytics and operational systems. Architect and optimize data infrastructure, including storage solutions, orchestration frameworks, and ETL/ELT processes. Ensure data quality, reliability, and security by establishing standards, monitoring systems, and implementing validation and governance practices. Lead and mentor data engineering staff, providing technical guidance, reviewing designs/code, and supporting professional growth. Collaborate with cross functional partners, such as data scientists, analysts, product teams, and business stakeholders, to ensure data solutions meet organizational needs and strategic goals.

Other Desired Skills: Must have a BS in Computer Science / Data Science / Information Systems with an overall 4+ years of experience in designing and implementing data, analytics, and AI solutions for large enterprises by building data pipelines using the available data platform tools of any Cloud Service Provider (CSP) such as AWS/Microsoft/Google.

o Experience of minimum 4 years in modeling and leveraging Relational data services with demonstrated proficiency in Python/Pysparks/SQL programming and tuning SQL queries to extract data from multiple sources ( relational DB, flat files, CSV, HTML, JSON, etc.) sources into Lakehouse Medallion architecture in parquet formats

o Demonstrated experience and expertise of minimum 4 years in programming/scripting languages including Python, R, Spark, etc.

o Experience in designing and delivering Star-schema based operational data store is required to enable visualization of program activities and outcomes in a visualization tool such as Power BI.