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Manager Data Engineering Jobs in Utah (NOW HIRING)

Utah Community Credit Union

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 ...

Utah Community Credit Union

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 ...

BambooHR

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 ...

Pwc

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 ...

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Showing results 21-40

All JobsData Engineering JobsManager Data Engineering JobsManager Data Engineering Jobs in Utah

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 are popular job titles related to Manager Data Engineering jobs in Utah?

For Manager Data Engineering jobs in Utah, the most frequently searched job titles 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:

Manager Data Engineering jobs near you
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.

Senior Software Engineer- Big Data & MCP, Data Foundations

RevSpring Inc

Salt Lake City, UT

$54 - $71.25/hr

Full-time

Re-posted 22 days ago

Job description

Job Title: Senior Software Engineer- Big Data amp; MCP, Data Foundations
Job Summary:
Essential Functions:
  • Collaborate and Innovate: Partner with product managers, data engineers, and business leaders to translate complex product and data requirements into scalable, reliable data pipelines and the search experiences they power.
  • Architect Data Pipelines: Design, build, and optimize large-scale distributed batch and streaming pipelines (using Apache Airflow, Apache Beam/Dataflow, and DBTon BigQuery) to ingest, model, and transform high-volume healthcare data into clean, well-tested, query-ready datasets and search indices.
  • Build Data Models amp; Backend Services: Develop resilient Python services and DBT models that power data delivery and self-service analytics, including Model Context Protocol (MCP) servers that expose curated data and tooling to downstream and AI consumers, and integrate with external REST/SOAP APIs and third-party data sources.
  • Optimize Data amp; Search Performance: Deeply tune pipeline throughput, data warehouse performance, and search indexing — optimizing BigQuery cost and query performance and Elasticsearch index design to ensure data freshness, relevance, and scalability across high-volume datasets.
  • Drive Engineering Excellence: Write clean, maintainable, well-tested code and lead by example through rigorous code reviews, architectural and data-modeling design discussions, and mentoring, driving a culture of high-quality software and trustworthy data.
  • Pioneer New Technologies: Stay at the forefront of modern data engineering, the analytics-engineering ecosystem (e.g., DBT, BigQuery), and information retrieval, proactively applying these advancements to strengthen our data platform and the products it powers.
Minimum Requirements:
Specific Job Skills:
  • Data Engineering: Proven experience designing and orchestrating large-scale ETL/ELT pipelines using Apache Beam/Google Cloud Dataflow (or similar), and DBT, built on modern cloud data warehouses. BigQuery experience is a plus.
  • Databases amp; SQL: 4+ years of experience working with relational databases and analytical data warehouses, with deep, advanced SQL skills and solid data-modeling fundamentals (e.g., dimensional and normalized modeling).
  • Search amp; Indexing: Working experience with search indexing and Elasticsearch, including index management, mappings, and building and maintaining search indices from pipeline output. Familiarity with hybrid (BM25 + semantic/vector) search is a plus.
  • Backend amp; Data Services: Experience building scalable Python services and high-performance data APIs, including developing Model Context Protocol (MCP) servers that expose data and tooling to downstream and AI consumers.
  • Infrastructure amp; DevOps: Strong understanding of containerization (Docker), CI/CD methodologies (e.g., GitHub Actions), Git, Infrastructure as Code (e.g., Terraform/Pulumi), and managing services within cloud platforms (3+ years of GCP experience preferred).
  • Familiarity with healthcare data standards (e.g., NPPES/NPI registries, NUCC Provider Taxonomy, machine-readable files (MRFs) for cost transparency, and FHIR).
  • Experience with data quality and pipeline testing frameworks (e.g., dbt tests, Great Expectations) and streaming/event ingestion (e.g., Pub/Sub, Kafka).
  • Experience integrating graph-based data and healthcare taxonomy ontologies to enrich datasets and search query context.
  • Experience with observability and logging platforms (e.g., DataDog) for monitoring pipeline health and data freshness.
Education: Bachelor’s Degree
Experience: 5+ years of professional experience with Python, with strong software-engineering fundamentals (testing, code review, design). 3+ years experience with Java or another JVM language is also high desired, particularly for Beam/Dataflow.
Supervision: N/A
Certifications: N/A
Language Skills:
Ability to read, analyze and interpret general business periodicals, professional journals, technical procedures or governmental regulations. Ability to write reports, business correspondence and procedure manuals. Ability to effectively present information and respond to questions from a variety of both internal and external sources.
Physical Capabilities: Standard categories
The physical capabilities described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
While performing the duties of this job, the employee is regularly required to sit; use hands to finger, handle, or feel; reach with hands and arms; and talk or hear. The employee is occasionally required to stand and walk. The employee must occasionally lift and/or move up to 10 pounds. Specific vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception, and ability to adjust focus.
RevSpring is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
Note: This Job Description may not describe all of the job responsibilities and standards assigned to this position. The duties may change from time to time. RevSpring does not discriminate against any group in hiring or employment practices. Nothing in this job description constitutes a contract for employment.

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