Data Engineer I

Larry H. Miller Company; Sandy (UT); On-site; USD 55,000 - 75,000; Full time

Job summary

Larry H. Miller Company is seeking an entry-level Data & Analytics teammate in Sandy, UT to help build and maintain reliable data pipelines and analytics-ready datasets. You will ingest data from diverse sources into Snowflake, organize raw to curated layers, and produce analyses for reporting and decision-making.

Responsibilities include improving data processes, ensuring data quality, and collaborating with analysts to implement business rules. Onsite role with growth in a dynamic data team.

Qualifications

• Bachelor’s degree or equivalent in a related field preferred.
• 0–2 years in data engineering, software development, analytics engineering, or related field.
• Strong SQL foundations with joins, CTEs, aggregations, and window functions.
• Experience with Python or another modern language and willingness to develop in Python.
• Familiarity with REST APIs, JSON/CSV, Git, testing, debugging, and code documentation.

Responsibilities

• Build and support data ingestion and transformation pipelines.
• Ensure reliability, accuracy, security, and usability of data for reporting and analytics.
• Improve data processes by reducing manual work and increasing efficiency.
• Schedule, monitor, and troubleshoot data jobs; review logs and incidents.
• Develop analytics-ready tables, views, data marts, and dimensional models for reporting.
• Collaborate with analysts and stakeholders to apply business rules and standard definitions.

Skills

SQL

Python

Snowflake

Git

REST APIs

JSON/CSV

ETL/ELT

dbt

Airflow

Control-M

AWS

Power BI

CI/CD

Docker

Linux

Data governance

Education

Bachelor’s degree in computer science, information systems, data engineering, data analytics, engineering, or related field

Equivalent education, training, internship, project, or work experience may be considered

Tools

Snowflake

Git

Job description

Entry-level role on the Data & Analytics team focused on building and supporting reliable data pipelines and analytics-ready datasets.

• Protect the legal, financial, and moral well-being of LHM and its portfolio companies
• Support reliability, accuracy, security, and usability of data used for reporting, analytics, applications, and business decision-making
• Improve data processes by reducing manual work and increasing operational efficiency
• Follow LHM policies, data-security practices, coding standards, and change-management processes
• Build, maintain, and support data ingestion and transformation pipelines using SQL, Python, and approved data-engineering tools
• Ingest data from databases, APIs, cloud storage, flat files, and other approved sources into Snowflake or related platforms
• Organize data into raw, staged, and curated layers aligned with established team standards
• Create reusable, parameterized, maintainable pipeline components instead of one-time manual processes
• Develop and maintain analytics-ready tables, views, data marts, and dimensional models for reporting and analysis
• Apply business rules and standard definitions in partnership with analysts and business stakeholders
• Implement data-quality checks for completeness, accuracy, duplicates, nulls, referential integrity, valid values, and unexpected record-volume changes
• Reconcile data between source systems and the data platform, investigate discrepancies, and document findings
• Schedule, monitor, and troubleshoot data jobs: review logs, identify root causes, document incidents, and elevate as appropriate
• Support pipeline alerts, retries, restart procedures, and other reliability practices
• Document data sources, refresh schedules, transformations, dependencies, ownership, and known limitations
• Create technical specifications, process diagrams, test plans, and deployment documentation
• Write and maintain unit, integration, regression, and data-validation tests; document test results
• Use Git, pull requests, code reviews, and established development, test, and production promotion practices
• Participate in technical design discussions and contribute to continuous improvement of the team’s data-engineering framework
• Assist with Snowflake performance and cost optimization by improving queries, models, workloads, and data structures
• Follow security and governance practices for sensitive financial, employee, customer, health, and other restricted data, including appropriate access controls and handling
• Collaborate with data analysts, BI developers, application teams, finance, HR, and other stakeholders to deliver reliable data
• Support production operations and participate in on-call or after-hours support when required by team practices
• Stay current with modern data-engineering practices as the LHM data platform evolves
• Perform other duties as assigned

Requirements

• Bachelor’s degree in computer science, information systems, data engineering, data analytics, engineering, or a related field preferred; equivalent education, training, internship, project, or work experience may be considered
• Zero to two years of experience in data engineering, software development, analytics engineering, database development, or a related field; relevant academic, internship, or portfolio projects may qualify
• Demonstrated ability to deliver a data, programming, database, or automation project from requirements through testing and documentation
• Strong foundation in SQL, including joins, common table expressions, aggregations, window functions, and basic query troubleshooting
• Working knowledge of Python or another modern programming language, with willingness to develop in Python
• Understanding of relational databases, data types, keys, normalization, and basic dimensional data-modeling concepts
• Understanding of ETL and ELT, including ingestion, transformation, loading, incremental processing, and data validation
• Familiarity with REST APIs and data formats such as JSON and CSV (or other common integration formats)
• Familiarity with Git, source control, testing, debugging, and code documentation
• Strong analytical and problem-solving skills, including investigating unexpected data results
• Strong attention to detail with commitment to data accuracy, security, and reliability
• Ability to communicate clearly in writing and verbally and tailor technical explanations to different audiences
• Ability to work collaboratively, accept feedback, manage priorities, and ask for help when appropriate

Technologies

• SQL, Python, Snowflake, Git
• REST APIs, JSON, CSV
• ETL, ELT, dbt
• Control-M, Airflow, Prefect
• AWS, S3, Lambda, Glue, Secrets Manager, SNS
• Power BI
• CI/CD, Docker, Linux
• Data cataloging, metadata, lineage, data-governance
• Dimensional data-modeling

Preferred knowledge and skills

• Experience with Snowflake or another cloud data warehouse
• Experience with dbt, Control-M, Airflow, Prefect, or another workflow-orchestration tool
• Experience with AWS services such as S3, Lambda, Glue, Secrets Manager, or SNS
• Experience with Power BI or other business‑intelligence platforms, especially data models and semantic layers
• Familiarity with CI/CD, Docker, Linux, cloud security, data cataloging, metadata, lineage, or data-governance practices
• Familiarity with operational data such as financial, ERP, HR, ticketing, sports, real estate, or health‑care
• Basic understanding of accounting concepts such as general ledger, debits and credits, trial balance, and financial statements

Education (additional)

• Preferred: Bachelor’s or better in Information Technology or related field

Reporting

• Reports to: Director of Data and Analytics

Work location and environment

• Onsite role in Sandy, UT
• Physical requirements: primarily office setting; regularly required to sit, stand, bend, reach, and move about facilities; may be required to perform other duties as assigned