Data Engineer - Enterprise Data Platform & Integrations

Ziegler Inc.

BLOOMINGTON (MN)

On-site

USD 95,000 - 119,000

Full time

14 days+

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Benefits offered by this job

Health, Dental, Vision and Life Insur.
15 days PTO first year
9 paid holidays
401(k) plan with company contribution
HSA contributions up to $1000/year
Disability Insurance, FSA & EAP
Paid Parental Leave & Funeral Leave
Fitness membership discount
Education Assistance

Job summary

Ziegler CAT in Bloomington, MN is seeking a Data Engineer to design, develop, and optimize the enterprise data platform, including Microsoft Fabric-based data warehouse and ETL/ELT pipelines, with on-premises work at the Bloomington office.

The role focuses on building scalable data architectures, ensuring data quality, and guiding integrations across ERP/CRM systems, BI tools, and cloud interfaces, while collaborating with stakeholders and mentoring teammates.

Qualifications

  • Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or related field; or equivalent experience.
  • 3+ years of experience in data engineering, data warehousing, ETL/ELT development, or related fields.
  • Experience designing and supporting enterprise data warehouse solutions.
  • Experience with Microsoft Fabric, Azure Data Services, or comparable cloud-based data platforms.
  • Strong proficiency with SQL and relational database design.
  • Experience developing and maintaining data integration solutions and enterprise interfaces.
  • Strong understanding of dimensional modeling, star schemas, and data warehouse architecture.
  • Experience working with data pipelines, orchestration tools, and data transformation frameworks.
  • Strong troubleshooting, problem-solving, and analytical skills.
  • Excellent communication skills with the ability to work effectively across multiple departments and organizational levels.
  • Self-starter with the ability to manage multiple priorities and projects.
  • Strong attention to detail and commitment to data quality.

Responsibilities

  • Design, develop, maintain, and optimize enterprise data warehouses and data platforms utilizing Microsoft Fabric.
  • Develop, manage, and monitor ETL/ELT pipelines that support operational reporting, analytics, business intelligence, and data integration initiatives.
  • Design and implement scalable data architectures that support current and future business needs.
  • Build and maintain integrations between ERP systems, CRM systems, cloud applications, third-party vendors, and internal business applications.
  • Collaborate with business stakeholders to understand data requirements and translate them into technical solutions.
  • Ensure data integrity, quality, consistency, and accuracy across enterprise systems.
  • Implement and maintain data governance, security, and compliance standards.
  • Monitor and troubleshoot data pipelines, integrations, and warehouse performance while proactively identifying improvement opportunities.
  • Develop and maintain data models, dimensional structures, and reporting datasets that support business intelligence initiatives.
  • Partner with Business Intelligence, Power BI, and application development teams to deliver reliable and performant data solutions.
  • Establish and enforce data engineering standards, development processes, and documentation practices.
  • Evaluate emerging technologies and recommend improvements to Ziegler's data platform and architecture.
  • Provide technical leadership, mentoring, and coaching to team members and new hires.

Skills

SQL
Analytical skills
Communication skills
Self-starter

Education

Bachelor's degree in Computer Science / Information Systems / Data Engineering or related field

Tools

Microsoft Fabric
Azure Data Services

Job description

Ziegler CAT in Bloomington, MN is seeking a Data Engineer to design, develop, and optimize the enterprise data platform, including Microsoft Fabric-based data warehouse and ETL/ELT pipelines, with on-premises work at the Bloomington office.

The role focuses on building scalable data architectures, ensuring data quality, and guiding integrations across ERP/CRM systems, BI tools, and cloud interfaces, while collaborating with stakeholders and mentoring teammates.

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