Cloud Data Architect & Lakehouse Engineering Lead

Value Innovation Labs; Lansing (MI); Hybrid; USD 140,000 - 200,000; Full time

Job summary

Value Innovation Labs is seeking an experienced Data Engineering Lead / Data Warehouse Architect to drive the design and implementation of scalable data pipelines and enterprise data platforms. The role focuses on building Lakehouse-based architectures, governance, and data products while coordinating cross-functional teams.

The ideal candidate will lead cloud data infrastructure efforts across AWS/Azure/GCP, utilize Databricks, PySpark, Spark, Python, SQL, and R, and mentor engineers to adopt

Qualifications

• Deep experience in enterprise data architecture and data engineering leadership.
• Hands-on with cloud platforms (AWS/Azure/GCP).
• Proficient in Databricks, PySpark, Spark, Python, SQL, and R.

Responsibilities

• Lead the design, development, and maintenance of enterprise data pipelines.
• Architect scalable cloud-based data infrastructure and Lakehouse solutions.
• Ensure data quality, security, governance, and data-sharing policies.
• Lead and mentor data engineering teams.
• Collaborate with data scientists, analysts, and business stakeholders.
• Drive data engineering standards and best practices.

Skills

Data Engineering

Data Modeling

DW Architecture

Cloud Platforms

Databricks

PySpark

Python

SQL

R

Lakehouse Architecture

ETL/ELT

Data Governance

Data Lake

Parquet

Kafka

Kubernetes

Docker

NoSQL

Graph DBs

AWS Glue

Redshift Spectrum

SageMaker

Power BI

Tableau

DBT

Terraform

GitHub

Jenkins

YAML

DAGs

Tools

Python

SQL

Spark

Job description

Value Innovation Labs is seeking an experienced Data Engineering Lead / Data Warehouse Architect to drive the design and implementation of scalable data pipelines and enterprise data platforms. The role focuses on building Lakehouse-based architectures, governance, and data products while coordinating cross-functional teams.

The ideal candidate will lead cloud data infrastructure efforts across AWS/Azure/GCP, utilize Databricks, PySpark, Spark, Python, SQL, and R, and mentor engineers to adopt