16342 - Data Warehouse Architect 3

Work Model: Hybrid, 2 days a week on site Allows Relocation: yes, but must still interview in person

SUMMARY 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.

RESPONSIBLITIES 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.

QUALIFICATIONS

Required:

· Minimum 4 years of hand-on experience is required in hydrating the enterprise Data Lake on a Cloud Service Provider (AWS, Azure, or Google) from relational, semi-structured and unstructured data sources by building Extract and Load Data Pipelines. · Minimum of 4 years hands-on experience is required in Transforming the datasets in a Data Lake on a Cloud Service Provider to deliver Data Products with traceability of their attributes / features to the Critical Data Elements in the systems of record. · Minimum of 2 years’ experience is required in enforcing Data Sharing Policies to Data Products to ensure that User get to see only the version of the Data Product the User is entitled to get access to at the time of subscription. · Bachelor’s Degree

Preferred:

· Proficiency desirable in DevOps tools including Github/Jenkins/Terraform/YAML/DAGs/Docker/Databricks/SageMaker etc. for building Data/ML pipelines to extract/store data from multiple sources to parquet destinations. · Experience desirable in promoting Data Engineering Standards and Best Practices among the community of developers to influence the enterprise towards building scalable and supportable Data/ML Products delivery and their usage by the community of data, analytics, and ML product users. · Experience desirable in implementing Data Governance and Data Security tools available on a CSP to automate the enforcement of Data Sharing Policies at the point of subscription of a Data Product by a subscriber.

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. · 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 · Demonstrated experience and expertise of minimum 4 years in programming/scripting languages including Python, R, Spark, etc. · 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. · Key Programming Languages: SQL, Python, R, Spark, Terraform Scripting, DAGs Scripting, YAML scripting, Docker · Other Technologies, Concepts and Frameworks: Juniper Notebooks, NOSQL DB, Graph DB, Parquet DB, Lakehouse and Medallion Architecture concepts, Kafka, Kubernetes, Glue, Databricks, Power BI, Tableau, Redshift Spectrum, Sagemaker, DBT, Datahub, SageMaker, Machine Learning, GitHub, DevOps

MANAGER NOTES

· Occasional travel to Ann Arbor for in-person meetings. · Potentially two rounds of client interviews. 1st would be virtual; 2nd in person. No exceptions.

PRE-EMPLOYEMENT & CLIENT SUBMISSION REQUIREMENTS

Employment and/or client submission is contingent upon successful completion of required pre-employment screening and verification processes. These requirements include:

• Background check: Candidates must successfully complete the required background screening in accordance with company policy and applicable law.

• Drug screening: Candidates must successfully complete the required drug screening in accordance with company policy, applicable client requirements, and applicable law.

• Identity and location verification: Candidates may be required to complete identity and/or location verification using a secure verification tool prior to client submission.

• Employment eligibility: Candidates must provide appropriate documentation to verify employment eligibility as required by law.

• Qualification verification: Information provided during the application and recruiting process, including employment history, education, certifications, licenses, and professional references, may be verified as applicable.

• Additional client requirements: Additional screening, documentation, or verification may be required based on the client, position, work location, or applicable requirements.

All screening and verification activities will be conducted in accordance with applicable company policies, client requirements, and federal, state, and local laws.

BENEFITS

This is a contract opportunity with a great organization. As a contractor for Smith Johnson, you are eligible for medical, dental, life, disability. Smith Johnson pays for 70% of your medical and dental and 100% of life and disability. The contract is also eligible for PTO/holiday accrued monthly. You are also eligible for a 3% retirement matching plan. Smith Johnson believes in taking care of our contractors.