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NeighborNeighborLehi, UT

Software Engineer, Data

Build, scale, and optimize data pipelines and infrastructure that transform raw events into actionable intelligence for analytics, BI, and business decisions. First dedicated data engineer on a small data team; own ingestion, transformation, semantic layer, and mentor analysts/scientists. Requires 5+ years software engineering with data emphasis, expert SQL, and data warehouse experience.

Salary not listed
On-site5+ YOEData Engineering

About the role

Primary Responsibilities

  • Design and build robust pipelines to ingest data from diverse sources (APIs, logs, relational DBs).
  • Ensure the reliable and timely execution of all critical data pipelines (ETLs/ELTs) to maintain data integrity and freshness.
  • Standardize analytics workflows by integrating software engineering best practices, including version control, CI/CD pipelines, and automated data validation protocols.
  • Develop and refine a robust semantic layer to facilitate self-service analytics, enabling stakeholders to derive insights without exposure to underlying architectural complexities.
  • Monitor and optimize cloud compute utilization and data model performance to ensure high availability and low-latency reporting during periods of rapid data scaling.
  • Serve as a strategic technical partner to leadership across Product, Engineering, Marketing, and Finance to align data infrastructure with organizational objectives.
  • Become a subject matter expert on the product ecosystem, user behavior, and marketing life cycles to better translate raw data into business value.
  • Go deep on analysis yourself when the question demands it; comfortable in both the pipeline and the insight.
  • Mentor our data analysts and data scientists on engineering best practices (code review, testing, version control, pipeline design), raising the technical bar across the team.

Qualifications

  • 5+ years as software engineer including 3+ years with an emphasis in data engineering or analytics engineering.
  • Bachelor's degree in quantitative and/or technical fields (Math, Physics, Statistics, Economics, Computer Science, Engineering, etc.) or equivalent practical experience.
  • Expert-level mastery of SQL, with the ability to write, tune, and optimize complex queries for high-volume environments.
  • Hands-on experience designing and maintaining data lakes or cloud-based data warehouses.
  • Deep understanding of data integration patterns, including data ingestion, transformation, and automated cleansing (ETL/ELT).
  • Advanced ability to translate complex datasets into actionable narratives using modern business intelligence and reporting tools.
  • A proven track record of using quantitative analysis to solve ambiguous problems and drive strategic decision-making in a fast-paced environment.
  • Exceptional ability to collaborate with non-technical stakeholders, translating business requirements into technical specs and vice versa.

Benefits

  • Generous Stock options
  • Medical, dental, and vision insurance
  • Generous PTO
  • 11 paid company holidays
  • 401(k) plan
  • Infant care leave
  • On-site gym/showers open 24/7

Stack

  • dbt and Dagster on Redshift and Athena, with Superset for BI.

Skills

SQLdbtDagsterRedshiftathenasupersetETLELTData Warehousingdata lakesCI/CDPython

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