Data Engineer II

McCarthy Holdings, Inc. (McCarthy), is the holding entity for McCarthy Building Companies, Inc., the oldest privately-held national construction company in America, and Castle Contracting. McCarthy provides the crucial business infrastructure for these entities and connects the day-to-day operations to ensure seamless operations across the business. Repeatedly honored as a great place to work and healthiest employer, McCarthy is a 100 percent employee-owned company.

At McCarthy, we are committed to sustaining a culture that delivers great experiences for everyone. This begins with developing high-performing individuals and teams through our award-winning learning and development programs, best-in-class Total Rewards benefits, and our inclusive culture aligned with our core values: Genuine; We, Not I and All In.

How do McCarthy partners define our culture?

We Live Our Core Values. We do whatever it takes to deliver on our promises with honesty and integrity.

We are Employee Owned. We are personally invested in supporting the success of the business.

We Feel Like a Family. We value genuine connections and help each other succeed in an inclusive environment.

We are Builders. We respect the work we do and everyone who helps make it happen safely.

Position Summary
McCarthy is seeking a full-time Data Engineer located in St. Louis, MO who, as part of the Enterprise Solutions and Analytics team, will play a crucial part in shaping our data infrastructure, supporting our existing systems, and driving innovation through ML and AI solutions. As we expand our capabilities, your expertise will be pivotal in delivering end-to-end data pipelines and repositories.

Key Responsibilities

• Profile source system data and design data warehouse and lake schemas
• Transform raw data into usable format based on analytics, reporting and integration requirements.
• Design, implement, and support ETL, ELT and integration pipelines
• Optimize data pipelines for performance, scalability and efficiency.
• Implement data quality checks and validations within data pipelines to ensure accuracy, consistency and completeness of data.
• Collaborate with cross-functional teams to promote AI solutions in the enterprise.
• Apply best practices in solution development, quality control and security in implementing pipelines.
• Participate in code and design review to ensure alignment to standards and best practices
• Research, analyze, recommend, and select technical approaches for solving challenging and complex development and integration problems

Qualifications

• 5+ years of work experience in data management disciplines, including data modeling, integration and development of ETL/ELT pipelines.
• 5+ years of data solution delivery experience, preferably in the Microsoft Azure platforms and tools (Azure Data Factory, Azure SQL, Azure Data Lake Gen2, Azure DevOps). Experience in Microsoft Fabric would be a plus.
• Experience with T-SQL (queries, stored procedures, and DDL)
• Experience querying API endpoints
• Experience with Power Query
• Solid understanding of data warehouse and data lake concepts and design (including star schemas)
• Experience with Agile/Scrum methodology preferred
• Excellent analytical, conceptual, and problem-solving abilities with aptitude for acquiring new technical skills
• Entrepreneurial attitude with a passion to deliver value for the organization
• Highly motivated team player with strong interpersonal skills
• Constant learner with a passion for continuous growth and improvement
• Python proficiency for data management, ML and AI development.

Additional Experience and Skills that are not required but would be beneficial:

• Experience developing integration solutions using a low-code platform such as Boomi, Snaplogic or Mulesoft.
• Experience developing solutions on Palantir
• Experience developing solutions in a Lakehouse platform
• Experience developing and promoting work through devops/dataops pipelines and utilizing source control
• Experience with NoSQL database systems and building data pipelines to ingest unstructured and streaming data
• Experience preparing data for Data Science and Machine Learning use cases
• Experience with master data management
• Experience designing reports using Power BI, Power Query, and DAX

McCarthy is proud to be an equal opportunity employer, including disability and protected veteran status.