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Data Warehouse Architect

Stellar Professionals LLCLansing, MI🇺🇸United States

Why this role stands out

Embark on a transformative data modernization journey with Stellar Professionals LLC, where you'll lead critical ETL migrations to a cutting-edge cloud platform. This role is perfect for a seasoned Data Warehouse Architect with deep expertise in IBM DataStage and cloud data solutions, offering significant impact and skill development within a reputable logistics company. You'll thrive in this hybrid environment, contributing to a vital enterprise initiative and gaining invaluable experience.

Quick overview

SeniorityMid Senior
Work modeOn Site
LocationLansing, MI, United States
DockerSQLGitApache SparkAWSTableauDatabricksGoogle CloudJenkinsKafkaPythonRedshiftTerraformdbtAzureKubernetesPower BI

Job description

We are looking for a hands-on Lead Data Engineer / Cloud Data Warehouse Architect to design, build, and optimize scalable cloud data pipelines, Lakehouse architectures, and enterprise data/ML products. In this position, you will establish data engineering best practices, enforce data governance policies, mentor engineering staff, and collaborate across data science and analytics teams.
Role: Lead Data Engineer / Cloud Data Warehouse Architect

Location: Lansing, MI (Onsite required from Day 1; occasional travel to Ann Arbor, MI)

Work Arrangement: Hybrid (Mandatory in-office on Wednesdays & Thursdays — no remote-only option)

Education: Bachelor’s Degree in Computer Science, Data Science, or Information Systems

About the Position

We are looking for a hands-on Lead Data Engineer / Cloud Data Warehouse Architect to design, build, and optimize scalable cloud data pipelines, Lakehouse architectures, and enterprise data/ML products. In this position, you will establish data engineering best practices, enforce data governance policies, mentor engineering staff, and collaborate across data science and analytics teams.

Must-Have Skills & Experience

  • Cloud Data Lake Engineering (4+ Years): Hands-on experience ingesting relational, semi-structured, and unstructured data into enterprise Data Lakes (AWS, Azure, or Google Cloud Platform) via Extract & Load pipelines.
  • Data Transformation & Lineage (4+ Years): Transforming cloud Data Lake datasets into production Data Products with clear traceability to Critical Data Elements (CDEs) in source systems.
  • Data Modeling & Programming (4+ Years): Strong proficiency in SQL, Python, PySpark, and R, query tuning, Star-schema operational data stores, and Lakehouse / Medallion Architecture (Parquet formats).
  • Data Governance & Access Control (2+ Years): Enforcing row/column-level Data Sharing Policies so subscribers only access entitled data versions.
  • Communication: Clear, concise written and verbal communication to lead technical discussions and mentor peers.

Preferred Tech Stack

  • Cloud & Big Data: Databricks, Spark, Kafka, AWS Glue, Redshift Spectrum, SageMaker, DBT
  • DevOps & Orchestration: Terraform, Docker, Kubernetes, GitHub, Jenkins, YAML, DAGs
  • Databases & BI: Relational, NoSQL, Graph DBs, Power BI, Tableau

Interview Process

  • Round 1: Virtual interview (Candidates must join from a laptop, be ready to share their screen, and provide a live verification photo).
  • Round 2: In-person interview in Lansing, MI.

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