Lead Data Engineer/Architect

IO Datasphere, Inc.; Lansing (MI); On-site; USD 90,000 - 130,000; Full time

Job summary

IO Datasphere, Inc. is seeking a senior data engineer in Lansing, MI to lead data modeling, Lakehouse architecture, and ML product delivery. The role requires deep experience with Spark, Kafka, Kubernetes, SageMaker, DBT, Docker, and SQL, plus strong visualization skills with Power BI/Tableau.

You will collaborate with Michigan DHHS and cross-functional teams in an agile DevOps environment. You will design and run data pipelines, ensure governance and security, and mentor junior engineers while

Qualifications

• 4+ years hands-on experience hydrating a Data Lake on AWS, Azure or GCP with ETL/ELT pipelines.
• 4+ years transforming datasets in a Data Lake to deliver data products with traceable attributes.
• 2+ years enforcing Data Sharing Policies for data products at subscription time.
• Experience with Spark, Kafka, Kubernetes, SageMaker, DBT, Docker, SQL.
• Experience with Power BI/Tableau for visualization.
• BS in Computer Science / Data Science / Information Systems with 4+ years overall.

Responsibilities

• Lead data engineering efforts with Lakehouse and ML product delivery in an agile DevOps setup.
• Engage with the State of Michigan proof-of-concept team to promote best practices.
• Oversee design, development, and maintenance of data pipelines for analytics and operations.
• Architect and optimize data infrastructure including storage and ETL/ELT processes.
• Ensure data quality, reliability, and security with governance practices.
• Mentor data engineers and collaborate with data scientists and product teams.

Skills

Data modeling

Lakehouse architecture

Distributed data

Spark

Kafka

Kubernetes

SageMaker

DBT

Python

SQL

Power BI

Tableau

DevOps

Data governance

Data security

Education

BS in Computer Science / Data Science / Information Systems

Tools

DataBricks

SageMaker

GitHub

Jenkins

Terraform

Docker

SQL

Spark

Kubernetes

Job description

If you are interested in this position:

Download the skills matrix using the button below and fill it out.
Email us and attach the completed skills form and your most recent resume to us at:
[e-mail]
Please include '10625MI Skills Form' and your name in the subject line.

Client Name Michigan Department of Health and Human Services (DHHS)

Requisition 168059

Location Lansing, MI

Duration 1 year

Due Date 11/19/2026

C2C Possible Yes. Rate depends on experience

Interview Method Webcam & Onsite

NOTE: Candidates must be local to the Lansing Michigan area and those willing to relocate. Candidates that relocate must relocate before day one and be ready to be on-site from day one at their own expense (non-negotiable). Wednesday and Thursday are REQUIRED in-office days. This is NON-NEGOTIABLE and there is NO remote only option. We can accept H1b, H4, TN and other valid work visas for IT. However we cannot accept OPT or CPT visas at this time.

Description:

Our client is looking a Data Engineer to 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:

Tasks

• 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.
• Serve 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.
• 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.

Knowledge, Skills and Abilities Required:

• Clear and concise written and verbal communication is crucial to success and productivity in this role

Skills Required

• 4+ years - 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.
• 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.
• 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.
• Experience in frameworks such as Spark, Kafka, Kubernetes, SageMaker, DBT, Juniper Notebooks, Docker, SQL
• Experience with visualization tools such as Power BI/Tableau with the following track record
• BS in Computer Science / Data Science / Information Systems with an overall 4+ years of experience
• 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.
• 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.