Data Analytics Engineer
About The Position
The Data Analytics Engineer is responsible for transforming raw and staged data into trusted, well-modeled, and analytics-ready datasets that empower reporting, dashboards, and data-driven decision-making across the organization. This role bridges the gap between engineering and analysis — ensuring data is clean, consistent, connected, and optimized for use by Analysts, BI Developers, and business teams. You will work closely with Data Engineers (who ingest data), BI Developers (who build dashboards), and Analysts (who generate insights) to build the semantic layer of the warehouse. You will own data modeling, cleansing, deduplication, and constructing unified datasets that bring together information from systems such as Salesforce, NetSuite, Google, and internal applications. This position is open to candidates located in the following states: Arizona (AZ), California (CA), Washington (WA), Nevada (NV), Utah (UT), Illinois (IL), Ohio (OH), New Jersey (NJ), Virginia (VA), North Carolina (NC), and Florida (FL).
Requirements
- Advanced SQL skills (window functions, CTEs, performance tuning).
- Experience with transformation frameworks (dbt strongly preferred).
- Strong understanding of data warehousing concepts: star schema, snowflake schema, fact/dimension modeling.
- Familiarity with cloud warehouses (Snowflake, BigQuery, Redshift, Synapse).
- Ability to troubleshoot mismatched metrics, broken joins, or duplicated data.
- Bachelor’s degree in Data Analytics, Computer Science, Information Systems, or related field.
- 3–5+ years of experience in analytics engineering, BI development, or data modeling.
Nice To Haves
- Experience with Python or R for data validation or automation scripts.
- Knowledge of BI tools (Power BI, Tableau, Looker) and how they interact with semantic layers.
- Familiarity with CI/CD for analytics code and version control (Git).
- Exposure to data governance, cataloging, and documentation tools.
Responsibilities
- Build, maintain, and optimize curated data models using SQL, dbt, or similar transformation tools.
- Create dimensional models (fact/dimension) and semantic layers to support reporting and advanced analytics.
- Construct unified datasets that bring together cross-system information (e.g., Salesforce, NetSuite, Google Ads).
- Profile, validate, and cleanse data to eliminate duplicates, missing fields, and inconsistencies.
- Implement automated data tests to ensure accuracy, completeness, and referential integrity.
- Investigate and resolve issues flagged by Analysts when metrics do not match or data looks incorrect.
- Partner with DBAs and Data Engineers to ensure performance at the warehouse structures and optimized queries.
- Adhere to and help define data governance, documentation standards, and semantic layer best practices.
- Maintain version-controlled analytics codebases using Git or similar workflows.
- Work closely with Analysts to understand their data needs and translate them into robust models.
- Support BI Developers by providing clean, reliable datasets that power dashboards and reports.
- Communicate issues, improvements, and data model changes clearly to technical and non-technical audiences.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
