Senior Analytics Engineer
Newfire Global Partners
full-time
Posted on:
Location Type: Remote
Location: United States
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Job Level
About the role
- Collaborate with data analysts, business stakeholders, and engineers to define, design, and build the critical data models that power business intelligence.
- Own the development, maintenance, and optimization of the data transformation layer using dbt.
- Design and implement scalable dimensional and fact models within Snowflake to support reporting, analysis, and data science use cases.
- Identify, investigate, and resolve data quality and performance issues within the data warehouse.
- Work closely with data consumers to understand their requirements and translate them into robust data structures and metrics definitions.
- Get to know the data as well or better than anyone else.
- As a Senior team member, you will be expected to actively participate in our hiring processes by serving on interview panels for future roles across the company.
Requirements
- Database Expertise (Snowflake): Deep experience with Snowflake's architecture, optimization, and advanced features (e.g., materialized views, clustering keys, query performance tuning).
- Expert dbt Proficiency: Demonstrated mastery in using dbt (Data Build Tool) for defining, testing, documenting, and deploying data transformation pipelines. Experience with dbt Cloud or similar CI/CD for data is a strong plus.
- Advanced Data Modeling: Strong conceptual and practical understanding of relational and dimensional modeling (e.g., Kimball methodology, normalization/denormalization) specifically tailored for analytical use cases.
- Expert SQL Skills: Ability to write complex, efficient, and optimized SQL queries for data transformation and analysis.
- Tableau Skills: Strong experience in connecting Tableau to Snowflake, developing high-impact dashboards, and optimizing Tableau workbook performance against large data sets. Fluency in other BI tools such as Sigma or Omni is a plus.
- Business Acumen: Experience modeling and engineering data related to marketing, product, and/or finance metrics. Experience with healthcare patient visits metrics is a strong plus.
- Communication: Ability to articulate technical constraints, data architecture choices, and data model logic clearly to both technical peers and business stakeholders.
- Data Governance & Quality Assurance: Meticulous attention to detail in QA processes, data lineage, and implementation of data quality checks (e.g., dbt tests).
- Requirements Translation: Experience translating abstract business questions into concrete, technical data model requirements.
- Ownership: Taking full responsibility for the integrity, performance, and reliability of the data models you build, ensuring stakeholders have complete trust in the data used for decision-making.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
SnowflakedbtSQLdata modelingdimensional modelingrelational modelingdata transformationdata qualitydata governancebusiness intelligence
Soft skills
communicationownershipcollaborationattention to detailbusiness acumenrequirements translation