Data Engineering Lead & Lakehouse Architect

IO Datasphere, Inc.; Lansing (MI); On-site; USD 90,000 - 140,000; Full time

Job summary

IO Datasphere, Inc. is seeking a Data Engineer to lead data modeling and pipeline delivery using Lakehouse and Medallion concepts. The role requires proficiency in Spark, Kafka, Kubernetes and ML/analytics tooling.

You will collaborate with Michigan DHHS and internal teams to ensure scalable, secure data products and governance across distributed systems while mentoring staff and driving DevOps practices.

Qualifications

• Extensive design and delivery of data pipelines in cloud environments.
• Experience with Lakehouse and Medallion architectures for analytics.
• Proficient in Python, PySpark, and SQL for data extraction and modeling.
• Hands-on with Spark, Kafka, Kubernetes, and ETL/ELT tooling.
• Strong communication and ability to train engineers and stakeholders.

Responsibilities

• Lead data engineering efforts and mentor staff in data lake and lakehouse projects.
• Architect, implement, and optimize data pipelines for analytics and ML workloads.
• Enforce data governance, quality, and security across data products.
• Collaborate with data scientists, analysts, and product teams for solutions.
• Oversee deployment and DevOps practices for scalable data/ML pipelines.

Skills

Data lake design

Lakehouse architectures

Medallion architecture

Spark

Kafka

Kubernetes

SageMaker

DBT

Juniper Notebooks

Docker

SQL

Power BI/Tableau

Python/PySpark/SQL

Education

BS in Computer Science / Data Science / Information Systems

Tools

DataBricks

Sagemaker

Spark

Kafka

Kubernetes

SQL

Power BI

Tableau

GitHub/Jenkins/Terraform

Job description

IO Datasphere, Inc. is seeking a Data Engineer to lead data modeling and pipeline delivery using Lakehouse and Medallion concepts. The role requires proficiency in Spark, Kafka, Kubernetes and ML/analytics tooling.

You will collaborate with Michigan DHHS and internal teams to ensure scalable, secure data products and governance across distributed systems while mentoring staff and driving DevOps practices.