Data Engineer

Description

Are you looking to be part of a high-performing team of go-getters who make a difference both on and off the court? Join the Detroit Pistons as we harness the power of basketball to unite our city, elevate our fans, and drive lasting community impact.

The Data Engineer is a key member of the Detroit Pistons Business Strategy & Analytics department, responsible for developing, maintaining, and optimizing the data infrastructure that supports business reporting, analytics, fan engagement, revenue generation, and operational decision-making across the organization.

This role will support the existing Microsoft SQL Server data warehouse while helping advance the organization’s transition to a modern data Lakehouse methodology leveraging Microsoft Fabric. The Data Engineer will work closely with the Senior Director of Data Strategy & Reporting to support the department’s data architecture, governance, reporting, and integration roadmap.

What You'll Be Doing

Data Architecture & Engineering

• Develop, maintain, and optimize data pipelines, data models, database objects, and integration processes within a Microsoft-based data environment.
• Assist in the transition from a traditional data warehouse structure to a modern data lakehouse methodology using Microsoft Fabric.
• Build scalable ETL/ELT processes to ingest, transform, validate, and deliver data for reporting, analytics, and business intelligence use cases.
• Support the design and implementation of Microsoft Fabric components, including OneLake, Lakehouse, Warehouse, Data Factory pipelines, Dataflows Gen2, notebooks, and Power BI integration.

Data Governance & Quality

• Support the Senior Director of Data Strategy & Reporting in implementing data governance standards, data quality processes, and enterprise data best practices.
• Develop and maintain data validation rules, reconciliation processes, and data quality checks across critical business datasets.
• Ensure data accuracy, consistency, integrity, privacy, and reliability across source systems, data warehouse objects, lakehouse assets, and reporting outputs.

Reporting & Analytics

• Prepare reliable, well-documented, and governed data assets to support reporting, analytics, automation, and AI applications.
• Support Power BI datasets, semantic models, dataflows, and reporting infrastructure as needed.
• Partner with analysts and business stakeholders to ensure data models meet business requirements, reporting standards, and performance expectations.

Data Management & Integration

• Integrate data from multiple internal and external systems into the organization’s data warehouse, data lakehouse, and analytics environment.
• Work with APIs, flat files, relational databases, SaaS platforms, and cloud-based systems to ensure reliable data ingestion and availability.
• Monitor pipeline health, investigate failures, and implement long-term solutions that improve reliability and reduce operational risk.
• Maintain clear technical documentation for integrations, refresh schedules, dependencies, data transformations, and business logic.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Engineering, or a related field preferred.
• Minimum of 4 years of professional experience in data engineering, database development, business intelligence, data warehousing, or a related data role.
• Experience working in a Microsoft data environment is required.

Skills & Competencies

• Strong proficiency with Microsoft SQL Server and MS SQL data warehouse environments.
• Advanced T-SQL skills, including stored procedures, views, joins, indexing, query optimization, and data modeling.
• Experience building ETL/ELT pipelines from multiple structured and semi-structured data sources.
• Strong understanding of data warehouse concepts, dimensional modeling, star schemas, data marts, and modern lakehouse methodologies.
• Familiarity with Microsoft Fabric, Azure Data Factory, Power BI, Azure SQL, Azure Data Lake, Synapse, or related Microsoft data tools.
• Experience with Python, PySpark, Spark SQL, or other modern data engineering languages and frameworks.
• Familiarity with preparing data for AI applications, including data quality, metadata, and secure access.
• Ability to translate business needs into scalable data engineering solutions.
• Ability to manage multiple priorities and deliver high-quality work in a fast-paced environment.

We are proud to be an Equal Opportunity Employer and are committed to fostering a diverse and inclusive workplace. Employment decisions are made without regard to race, color, religion, national origin, sex, sexual orientation, gender identity or expression, age, marital status, veteran status, disability, or any other characteristic protected by applicable federal, state, or local law.

We are dedicated to ensuring equal access throughout the employment process. Reasonable accommodations will be provided to qualified individuals with disabilities to enable participation in the application and interview process, to perform essential job functions, and to receive other benefits and privileges of employment. If you require an accommodation, please contact us to request assistance.