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Data Analytics Engineer Jobs in Draper, UT (NOW HIRING)

Data Analyst Assistant

American Fork, UT ยท On-site

$20 - $22/hr

Data Analyst Assistant (Part-time, 20 hours/week) - Programming Focus Location: American Fork, Utah (In Office) About Us: Brevium is a dynamic and innovative healthcare technology company located in ...

Data Analyst Assistant

American Fork, UT ยท On-site

$20 - $22/hr

Data Analyst Assistant (Part-time, 20 hours/week) - Programming Focus Location: American Fork, Utah (In Office) About Us: Brevium is a dynamic and innovative healthcare technology company located in ...

Direct and manage a small team of contractors: an Analytics Engineer responsible for data pipeline and infrastructure work, and a Tagging amp; Tracking Specialist responsible for implementation and ...

Direct and manage a small team of contractors: an Analytics Engineer responsible for data pipeline and infrastructure work, and a Tagging & Tracking Specialist responsible for implementation and QA. ...

Sr. Data Engineer

Draper, UT

$107K - $128K/yr

We'll rely on your expertise across data, analytics, ML, and AI engineering to develop, automate, and maintain pipelines and intelligent systems. Your ability to use AI in building reliable ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate & Summary The Opportunity As a Data Engineer - Senior Associate, you will focus on designing and ...

Data Solutions Engineer

Salt Lake City, UT ยท On-site

$98K - $160K/yr

Overview The Data Solutions Engineer will play a key role in integrating, architecting, and optimizing data systems to support data monetization, analytics, machine learning, artificial intelligence ...

Senior Data Engineer

Midvale, UT ยท On-site

$100K - $135K/yr

Enable conversational access to data so business users and analysts can explore datasets, ask ... Partner with data analysts, engineers, DevOps, and business stakeholders to deliver trusted data ...

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Data Analytics Engineer information

See Draper, UT salary details

$41.6K

$121.3K

$165.9K

How much do data analytics engineer jobs pay per year?

As of Jul 15, 2026, the average yearly pay for data analytics engineer in Draper, UT is $121,265.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,000.00 and $128,500.00 per year, depending on experience, location, and employer.

How do Data Analytics Engineers typically collaborate with data scientists and business stakeholders on projects?

Data Analytics Engineers play a crucial role in bridging the gap between raw data and actionable insights by building, optimizing, and maintaining data pipelines. They often work closely with data scientists to ensure data is clean, accessible, and structured for advanced analytics or machine learning models. Additionally, they collaborate with business stakeholders to understand reporting requirements and ensure that data solutions align with organizational objectives. Regular communication and cross-functional teamwork are essential aspects of this role, as engineers must translate business needs into technical specifications and deliver reliable data products.

Can a data engineer make 200k?

Data engineers can earn $200,000 or more annually, especially with experience, advanced skills in cloud platforms, big data tools, and certifications. Salaries vary by location, industry, and company size, with senior roles and those in high-demand markets more likely to reach or exceed this level.

What engineers make $500,000?

Senior data analytics engineers with extensive experience, advanced skills in data modeling, machine learning, and proficiency with tools like Python, SQL, and cloud platforms can reach salaries of $500,000 or more, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires a combination of technical expertise, leadership roles, and sometimes equity compensation.

What are the key skills and qualifications needed to thrive as a Data Analytics Engineer, and why are they important?

To thrive as a Data Analytics Engineer, you need strong proficiency in data modeling, SQL, and statistical analysis, typically supported by a degree in computer science, statistics, or a related field. Familiarity with tools such as Python, R, Apache Spark, Tableau, and cloud data platforms like AWS or Google BigQuery is essential, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills help you translate data insights into actionable business solutions. These skills and qualities are crucial for designing robust data pipelines and enabling data-driven decision-making across organizations.

Is 40 too late for data science?

Data Analytics Engineers and data science professionals can successfully transition into the field at age 40 or older, as skills such as programming, statistical analysis, and experience with tools like Python or SQL are valuable regardless of age. Many employers value diverse experience and lifelong learning, and certifications or online courses can help enhance credentials at any age.

What is the difference between Data Analytics Engineer vs Data Scientist?

AspectData Analytics EngineerData Scientist
CredentialsBachelor's or master's in CS, Data Science, or related fields; certifications like Google Data AnalyticsBachelor's or master's in CS, Statistics, or related fields; certifications like Certified Data Scientist
Work EnvironmentFocus on building data pipelines, dashboards, and analytics toolsFocus on statistical modeling, machine learning, and data exploration
Employer & Industry UsageUsed across tech, finance, healthcare for data infrastructure and analyticsCommon in research, product development, and advanced analytics teams

While both roles work with data, Data Analytics Engineers primarily develop data infrastructure and tools for analysis, whereas Data Scientists focus on statistical modeling and machine learning to generate insights. They often collaborate but have distinct technical focuses.

What does a data analytics engineer do?

A data analytics engineer designs, builds, and maintains data pipelines and systems to collect, process, and analyze large datasets. They use tools like SQL, Python, and cloud platforms to enable data-driven decision-making and often collaborate with data scientists and business teams to deliver actionable insights.
What are the most commonly searched types of Data Analytics Engineer jobs in Draper, UT? The most popular types of Data Analytics Engineer jobs in Draper, UT are:
What job categories do people searching Data Analytics Engineer jobs in Draper, UT look for? The top searched job categories for Data Analytics Engineer jobs in Draper, UT are:
What cities near Draper, UT are hiring for Data Analytics Engineer jobs? Cities near Draper, UT with the most Data Analytics Engineer job openings:
Infographic showing various Data Analytics Engineer job openings in Draper, UT as of July 2026, with employment types broken down into 1% Internship, 91% Full Time, 6% Part Time, and 2% Contract. Highlights an 82% Physical, 4% Hybrid, and 14% Remote job distribution, with an average salary of $121,265 per year, or $58.3 per hour.
Senior Software Engineer- Big Data & MCP, Data Foundations

Senior Software Engineer- Big Data & MCP, Data Foundations

RevSpring

Salt Lake City, UT โ€ข On-site

$110K - $133K/yr

Full-time

Posted 15 days ago


Job description

Job Summary:
RevSpring is a company focused on providing innovative data solutions, and they are seeking a Senior Software Engineer specializing in Big Data and data foundations. The role involves designing and optimizing data pipelines, developing backend services, and ensuring data performance and quality in a healthcare context.
Responsibilities:
โ€ข 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.
โ€ข 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.
โ€ข Build Data Models & 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.
โ€ข Optimize Data & Search Performance: Deeply tune pipeline throughput, data warehouse performance, and search indexing โ€” optimizing BigQuery cost and query performance and Elasticsearch index design to ensure data freshness, relevance, and scalability across high-volume datasets.
โ€ข 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.
โ€ข 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.
Qualifications:
Required:
โ€ข 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.
โ€ข 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).
โ€ข Working experience with search indexing and Elasticsearch, including index management, mappings, and building and maintaining search indices from pipeline output.
โ€ข 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.
โ€ข 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.
โ€ข Familiarity with healthcare data standards (e.g., NPPES/NPI registries, NUCC Provider Taxonomy, machine-readable files (MRFs) for cost transparency, and FHIR).
โ€ข Experience with data quality and pipeline testing frameworks (e.g., dbt tests, Great Expectations) and streaming/event ingestion (e.g., Pub/Sub, Kafka).
โ€ข Experience integrating graph-based data and healthcare taxonomy ontologies to enrich datasets and search query context.
โ€ข Experience with observability and logging platforms (e.g., DataDog) for monitoring pipeline health and data freshness.
โ€ข Bachelorโ€™s Degree
โ€ข 5+ years of professional experience with Python, with strong software-engineering fundamentals (testing, code review, design).
โ€ข 3+ years experience with Java or another JVM language is also high desired, particularly for Beam/Dataflow.
โ€ข Ability to read, analyze and interpret general business periodicals, professional journals, technical procedures or governmental regulations.
โ€ข Ability to write reports, business correspondence and procedure manuals.
โ€ข Ability to effectively present information and respond to questions from a variety of both internal and external sources.
Preferred:
โ€ข BigQuery experience is a plus.
โ€ข Familiarity with hybrid (BM25 + semantic/vector) search is a plus.
โ€ข 3+ years of GCP experience preferred.
Company:
RevSpring is a provider of revenue cycle technology services offering data analytics, multi-channel customer communications. Founded in 1997, the company is headquartered in Wixom, USA, with a team of 501-1000 employees. The company is currently Late Stage.