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Manager Data Engineering Jobs in Utah (NOW HIRING)

Data Engineer

Provo, UT · On-site

$108K - $130K/yr

... data management • Exposure to machine learning pipelines and feature engineering for predictive models • Experience with BI platforms such as Power BI, Tableau, or Looker • Relevant ...

Sr. Data Engineer

Draper, UT · Hybrid

$107K - $128K/yr

We'll rely on your expertise across data, AI, and knowledge engineering to develop reliable systems ... Design and manage cloud-based data and AI infrastructure (Databricks preferred), including ...

Data Strategy-Manager

Salt Lake City, UT · On-site

$99K - $232K/yr

... Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified Professional - Alation Certified Data ...

Data Engineer

Salt Lake City, UT · On-site

$105K - $126K/yr

Bachelor's degree in computer science, data engineering, information systems, or equivalent technical degree. * 3+ years of data engineering experience, specifically in managing a data warehouse.

Data Engineer

Salt Lake City, UT

$105K - $126K/yr

Bachelor's degree in computer science, data engineering, information systems, or equivalent technical degree. * 3+ years of data engineering experience, specifically in managing a data warehouse.

Showing results 21-40

Manager Data Engineering information

What are the roles and responsibilities of a manager data engineering?

A Manager Data Engineering oversees teams that design, build, and maintain data infrastructure and pipelines for organizations. They are responsible for ensuring the efficient flow and storage of data, implementing best practices in data management, and collaborating with stakeholders to meet business data needs. Additionally, they mentor and guide data engineers, manage project timelines, and ensure data security and quality standards are met. Their role often involves strategic planning to enable data-driven decision making across the company.

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

To thrive as a Manager Data Engineering, you need expertise in data architecture, advanced analytics, and leadership, typically supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop, Spark), data warehousing systems, cloud platforms (AWS, Azure), and certifications such as AWS Certified Data Analytics are highly valued. Strong communication, problem-solving, and team management skills help drive project success and foster collaboration. These skills ensure effective data solutions, alignment with business goals, and the ability to lead and grow high-performing engineering teams.

How does a manager data engineering typically collaborate with data scientists and business stakeholders?

A Manager of Data Engineering often serves as a bridge between technical teams and business stakeholders. They work closely with data scientists to ensure that data pipelines and infrastructure meet analytical needs, while also translating business requirements into actionable engineering solutions. Regular coordination meetings, clear documentation, and cross-functional projects are common, enabling seamless collaboration and alignment on goals. This role requires strong communication skills and the ability to balance technical priorities with business objectives.

What is the difference between Manager Data Engineering vs Data Engineer?

AspectManager Data EngineeringData Engineer
Required CredentialsBachelor's or Master's in CS, Data Science, or related; often leadership experienceBachelor's or higher in CS, IT, or related; technical certifications optional
Work EnvironmentTeam leadership, project management, strategic planningData pipeline development, coding, data modeling
Employer & Industry UsageTech companies, finance, healthcare, where data teams are commonData-focused roles across various industries

The main difference is that Manager Data Engineering oversees data teams and projects, focusing on strategy and leadership, while Data Engineers handle the technical implementation of data pipelines and infrastructure. Managers typically have more experience and leadership skills, whereas Data Engineers are more hands-on with coding and data architecture.

What are the most commonly searched types of Data Engineering jobs in Utah?

The most popular types of Data Engineering jobs in Utah are:

What job categories do people searching Manager Data Engineering jobs in Utah look for?

The top searched job categories for Manager Data Engineering jobs in Utah are:

What cities in Utah are hiring for Manager Data Engineering jobs?

Cities in Utah with the most Manager Data Engineering job openings:

Infographic showing various Manager Data Engineering job openings in Utah as of August 2026, with employment types broken down into 80% Full Time, 19% Part Time, and 1% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution.

Data Engineer

Provo, UT • On-site

Utah Community Credit Union
Commercial Banking • 501 - 1,000 employees

$108K - $130K/yr

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

The Data Engineer will own the design, development, and optimization of the data infrastructure that underpins analytics, reporting, and machine learning initiatives across the credit union. Working closely with business intelligence analysts, compliance teams, and technology leadership, this role requires both technical depth and the ability to translate complex data challenges into reliable, scalable solutions within a regulated financial environment.
ESSENTIAL FUNCTIONS AND BASIC DUTIES
• Architect, build, and maintain robust ETL/ELT pipelines to integrate data from core banking systems, lending platforms, digital banking channels, and third-party vendors
• Design and manage the credit union's data warehouse and data lake, including schema design, partitioning strategies, and performance optimization
• Develop and enforce data quality frameworks, including automated testing, validation rules, and alerting for pipeline anomalies
• Lead the implementation of data modeling best practices (dimensional modeling, data vault, or similar) to support scalable analytics
• Collaborate with data analysts, compliance officers, and business stakeholders to define data requirements and deliver trusted data products
• Manage orchestration and scheduling of data workflows using tools such as Matillion, Snowflake, or equivalent
• Evaluate, implement, and maintain cloud data infrastructure on Snowflake or Azure, including compute, storage, and networking resources
• Ensure all data processes comply with applicable regulations, including NCUA guidelines, BSA/AML requirements, and GLBA data privacy standards
• Partner with the IT security team to enforce data access controls, encryption standards, and audit logging
• Mentor junior data engineers and analysts, providing technical guidance and code reviews
• Drive adoption of DataOps practices, including CI/CD for data pipelines, version control, and documentation standards
• Support data migration efforts during platform transitions, core system upgrades, or mergers and acquisitions
• Works a regular and predictable schedule.
QUALIFICATIONS
REQUIRED QUALIFICATIONS
• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field (or equivalent professional experience)
• 3-5 years of hands-on experience in data engineering, data infrastructure, or a closely related role
• Advanced proficiency in SQL and experience with large-scale relational and columnar databases (e.g., PostgreSQL, Redshift, Snowflake, BigQuery)
• Strong Python skills for data pipeline development and automation
• Demonstrated experience designing and maintaining ETL/ELT workflows using tools such as dbt or Matillion
• Working knowledge of at least one major cloud platform (Snowflake, AWS, Azure, or GCP) and associated data services
• Solid understanding of data warehousing concepts including dimensional modeling and schema design
• Experience implementing data quality monitoring, lineage tracking, and observability practices
• Strong communication skills with the ability to work effectively across technical and non-technical audiences
PREFERRED QUALIFICATIONS
• Experience in a regulated financial services environment such as credit unions, banks, or fintech companies
• Familiarity with credit union core banking platforms such as Symitar (Episys), Jack Henry, or FiServ
• Knowledge of data governance frameworks, or master data management
• Exposure to machine learning pipelines and feature engineering for predictive models
• Experience with BI platforms such as Power BI, Tableau, or Looker
• Relevant certifications such as AWS Certified Data Analytics, Snowflake SnowPro, or dbt Certified Developer
• Familiarity with NCUA examination processes or financial regulatory reporting (e.g., HMDA, Call Report data)
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.