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Data Engineer Manager Jobs in Montana (NOW HIRING)

Data Engineer - Billings

Billings, MT · On-site

$112K - $135K/yr

The Data Engineer is expected to possess strong analytical and problem-solving skills, attention to detail, and the ability to manage multiple priorities while delivering accurate and dependable data ...

ABOUT THIS ROLE The Staff Data Engineer is a senior leader responsible for designing and evolving ... Build and maintain automation for compaction, retention, lifecycle management, and cost controls

ABOUT THIS ROLE The Staff Data Engineer is a senior leader responsible for designing and evolving ... Build and maintain automation for compaction, retention, lifecycle management, and cost controls

Incorporate agile methodologies and project management best practices to ensure timely delivery of highquality, secure, and scalable solutions. * Data Engineering & Advanced Analytics : Design and ...

New

Incorporate agile methodologies and project management best practices to ensure timely delivery of high-quality, secure, and scalable solutions. * Data Engineering & Advanced Analytics : Design and ...

New

Incorporate agile methodologies and project management best practices to ensure timely delivery of high‑quality, secure, and scalable solutions. * Data Engineering & Advanced Analytics : Design and ...

New

Incorporate agile methodologies and project management best practices to ensure timely delivery of high-quality, secure, and scalable solutions. * Data Engineering & Advanced Analytics : Design and ...

New

Team Management & Development * Lead and evolve a team of Engineering Managers and Software ... Coordinate with Data Engineering and Business Intelligence to ensure accurate measurements of ...

Project Manager - Data Center

Bozeman, MT · On-site

$126K/yr

Description CompuNet is seeking a Project Manager to join our Data Center Practice, an experienced team of Architects and Engineers who require project management support in their delivery of ...

Team Management & Development * Lead and evolve a team of Engineering Managers and Software ... Coordinate with Data Engineering and Business Intelligence to ensure accurate measurements of ...

OEM Technical Data & Resource Development Coordination * Act as a primary coordination point between OEM factory product managers and the domestic engineering team. * Coordinate acquisition of ...

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Showing results 1-20

Data Engineer Manager information

See Montana salary details

$40.8K

$119.1K

$162.9K

How much do data engineer manager jobs pay per year?

As of Sep 11, 2026, the average yearly pay for data engineer manager in Montana is $119,060.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,100.00 and $126,200.00 per year, depending on experience, location, and employer.

What does a data engineer manager do?

A Data Engineer Manager leads a team of data engineers to design, build, and maintain data pipelines and infrastructure. They collaborate with data scientists, analysts, and business stakeholders to ensure efficient data processing and accessibility. Their responsibilities include project management, team leadership, system architecture decisions, and optimizing data workflows. Additionally, they enforce best practices for data governance, security, and scalability.

What are the key skills and qualifications needed to thrive as a data engineer manager?

To thrive as a Data Engineer Manager, you need robust experience in data architecture, pipeline design, team leadership, and a relevant degree in computer science or a related field. Proficiency with cloud platforms (like AWS or Azure), big data tools (such as Hadoop, Spark), and certifications in data engineering or project management are highly valued. Strong soft skills like effective communication, problem-solving, and mentorship set exceptional managers apart. These competencies enable strategic oversight of technical teams and ensure reliable, scalable data solutions that meet business objectives.

What are some typical challenges a data engineer manager faces in their role?

Data Engineer Managers often face the challenge of balancing technical project delivery with team development and stakeholder management. They must ensure data systems remain scalable and reliable while adapting to evolving business requirements and new technologies. Additionally, managing cross-functional communication between data engineers, analysts, and business leaders can require strong organizational and interpersonal skills. Success in this role requires staying current with industry trends and fostering a collaborative, innovative team culture.

How much does a data engineer manager make?

A data engineer manager typically earns between $110,000 and $160,000 annually, depending on experience, location, and company size. They often oversee data teams, manage data pipelines, and require strong skills in SQL, cloud platforms, and leadership. Salaries can vary based on industry demand and certifications held.

What are the most commonly searched types of Data Engineer jobs in Montana?

The most popular types of Data Engineer jobs in Montana are:

What are popular job titles related to Data Engineer Manager jobs in Montana?

For Data Engineer Manager jobs in Montana, the most frequently searched job titles are:

What job categories do people searching Data Engineer Manager jobs in Montana look for?

The top searched job categories for Data Engineer Manager jobs in Montana are:

What cities in Montana are hiring for Data Engineer Manager jobs?

Cities in Montana with the most Data Engineer Manager job openings:

Infographic showing various Data Engineer Manager job openings in Montana as of June 2026, with employment types broken down into 1% As Needed, 53% Full Time, 41% Part Time, 1% Temporary, 3% Contract, and 1% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $119,060 per year, or $57.2 per hour.

Data Engineer - Billings

Billings, MT • On-site

$112K - $135K/yr

Other

Posted 7 days ago


Job description

Position Summary

The Data Engineer supports the Bank's enterprise data environment by building and maintaining data pipelines, preparing data for reporting and analytics, and improving data quality and reliability. This role works closely with Technology, Operations, and business teams to move data from banking systems into secure, reliable, and usable reporting structures.

The position is hands-on and execution-focused, supporting data warehousing, reporting, analytics, governance, and emerging artificial intelligence initiatives. The Data Engineer is expected to possess strong analytical and problem-solving skills, attention to detail, and the ability to manage multiple priorities while delivering accurate and dependable data solutions.

Data Engineer Responsibilities Data Pipeline Development
  • Build and maintain data pipelines for reporting and analytics.
  • Support data ingestion from core banking and related business systems.
  • Write, test, and maintain SQL queries, stored procedures, and scripts.
  • Document data flows, source data, and transformation logic.
Data Platform Support
  • Support the Bank's data warehouse, lakehouse, and reporting data structures.
  • Assist with Microsoft Fabric, Power BI, and related data platform initiatives.
  • Monitor scheduled jobs and resolve data processing issues.
  • Improve performance, reliability, and repeatability of production data processes.
Banking Systems Integration
  • Work with data from core banking, digital banking, credit card, mortgage, financial, and third-party systems.
  • Help define secure and maintainable data feeds.
  • Coordinate with system owners, vendors, and technology teams to investigate and resolve data issues.
Data Governance Enablement
  • Apply data quality controls and resolve data exceptions.
  • Maintain metadata, data definitions, and source documentation.
  • Support data governance efforts and regulatory requirements.
  • Ensure adherence to security, privacy, and data management standards.
Analytics Platform Support
  • Prepare trusted datasets for Power BI dashboards, reports, and management reporting.
  • Partner with business teams to understand reporting requirements and data needs.
  • Automate recurring reporting processes and reduce manual data preparation.
  • Support future analytics, machine learning, and AI initiatives through improved data readiness.
Team Collaboration
  • Work closely with Technology, Operations, and business teams.
  • Communicate technical issues in clear and practical business terms.
  • Follow established standards for change management, security, and documentation.
  • Continue developing expertise in data architecture, governance, and cloud-based data platforms.

Qualifications

Technical Qualifications
  • Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related technical discipline, or an equivalent combination of education and work experience.
  • Two to four years of experience in data engineering, business intelligence, database development, reporting, or data warehouse support.
  • Strong SQL skills.
  • Experience building or supporting ETL/ELT processes.
  • Working knowledge of relational databases and data modeling concepts.
  • Experience with Power BI or similar reporting platforms.
  • Python, PowerShell, or similar scripting experience preferred.
  • Microsoft Fabric or Azure Data Factory experience preferred.
  • Ability to troubleshoot data issues and document findings clearly.
Data and Banking Knowledge
  • Understanding of data warehouse design and reporting structures.
  • Familiarity with dimensional modeling, data quality, data lineage, and metadata concepts.
  • Core banking systems experience preferred.
  • Regulatory reporting experience preferred.
  • Financial institution data environment experience preferred.
  • Banking operations process knowledge preferred.
Success Measures
  • Reliable data pipelines and scheduled data processing jobs.
  • Improved data quality and reduced reporting exceptions.
  • Clear documentation of data sources, transformations, and business logic.
  • Reduced manual effort in recurring management reporting.
  • Continued growth in banking data knowledge and platform capabilities.

For full description, which includes physical mental demands please see attachment.

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