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Software Engineer, Data
Neighbor
Lehi, USA
Full-time
Senior Level
Onsite
Discovered 1 weeks ago
Free
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- 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, you're 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
- 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
- Generous Stock options
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