Sr Data Engineer

Description

Our client is looking for a Senior Data Engineer to lead the development of a scalable enterprise data environment that supports reporting, analytics, and informed decision-making across a nationwide organization. In this role, you will bring together data from multiple business platforms, create trusted structures for analysis, and help teams move from manual reporting methods to dependable automated solutions. You will work closely with leaders across finance, sales, and operations to define consistent data standards and deliver high-quality datasets for business intelligence and advanced analytics. This position is based in Southfield, Michigan.

Responsibilities:

Design and maintain enterprise data warehouse solutions that centralize information from multiple platforms and operational systems.

Build and optimize ETL and data ingestion workflows using tools and frameworks such as Python, Apache Spark, Kafka, and Hadoop.

Develop governed data models that improve consistency, accuracy, and usability for executive reporting, financial analysis, and self-service BI.

Partner with finance, sales, and operations stakeholders to align business definitions and translate reporting needs into reliable data assets.

Automate data consolidation processes to reduce manual effort and strengthen auditability across acquired and distributed business units.

Monitor data pipelines and warehouse performance, troubleshooting issues and implementing improvements to ensure stability and scalability.

Support analytics initiatives by preparing structured datasets for dashboards, ad hoc analysis, and emerging AI-enabled use cases.

Collaborate with BI teams to deliver data sources that integrate effectively with reporting tools such as Power BI.

Requirements

5+ years of experience in data engineering, data warehousing, or a closely related field.
Strong hands-on expertise with Python and SQL for building, transforming, and managing large-scale datasets.
Experience working with Apache Spark, Apache Hadoop, and Apache Kafka in data pipeline or distributed processing environments.
Proven background designing ETL processes and enterprise-grade data warehouse architectures.
Familiarity with cloud-based databases and modern data platforms.
Experience supporting business intelligence and reporting solutions, including Power BI or comparable BI tools.
Ability to work cross-functionally with business and technical stakeholders to define data standards and reporting requirements.

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