Senior Analytics Engineer

Digible, Inc

Senior Analytics Engineer building governed Silver/Gold data models and BI for Digible’s multifamily digital marketing platform. Owning semantic-layer standards, warehouse performance, and trusted self-serve analytics.

Posted 8/5/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $140,000 - $160,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Expertise in data warehouse strategy, performance optimization, and governance, with a strong focus on SQL, data modeling, and BI tooling. Proven ability to lead cross-functional collaboration and deliver standardized metrics and analytics solutions.

Highest-signal resume keywords

SQL ProficiencyData Modeling Tools (dbt, Dataform, SQLMesh)Cloud Data Warehouse Experience (Snowflake, BigQuery)BI Tools (Tableau, Looker, Hex)Dimensional Modeling and Medallion Architectures

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Warehouse StrategyPerformance OptimizationData ModelingSemantic Layer GovernanceMetric StandardizationPython for TransformationGit and Version ControlAI-Assisted Development ToolsCost OptimizationTroubleshooting Data Quality

Soft Skills

Strong Communication SkillsCross-Functional CollaborationStakeholder PartnershipProblem-SolvingTeamwork

Tools & Technologies

DbtSnowflakeBigQueryTableauLookerHexSigmaOmniMetabaseLightdash

Industry Keywords

Data WarehouseAnalytics EngineeringBI Tooling StrategyGovernance StandardsMetric Definitions

Tech Stack

Tools & technologies

BigQueryCloudPythonSQLTableau

About the role

Key responsibilities & impact

Drive data warehouse strategy and performance, including modeling standards, materialization strategy, query performance, and warehouse speed and cost optimization
Own Silver- and Gold-layer modeling in dbt, including clean, documented, tested, and governed models
Consolidate redundant pre-materialized views, resolve metric drift, and correct non-additive measures at risk of bad re-aggregation
Build and govern the semantic layer as a single source of truth for metric definitions
Lead BI tooling strategy and enablement, standardizing the BI stack and enabling trustworthy self-serve analytics
Partner with stakeholders and analysts to translate business questions into durable models and metrics
Establish data best practices, governance standards, and tooling for upstream domain teams
Troubleshoot data quality and consistency issues and drive root-cause, long-term fixes
Contribute to platform evolution by optimizing, refactoring, and scaling analytics infrastructure
Report to the Director of Data and partner with Data Engineering, Product, Engineering, analysts, and business stakeholders
Deliver governed metrics, performant Silver and Gold models, and standardized BI that reduce one-off data pulls and metric disputes

Requirements

What you’ll need

5-7+ years of data/analytics engineering experience, including at least 2 years in a senior capacity
Expert proficiency with SQL and data modeling tools such as dbt, Dataform, or SQLMesh
Strong command of dimensional modeling and medallion/layered architectures
Hands-on experience with at least one cloud data warehouse, such as Snowflake and/or BigQuery
Experience with data warehouse performance and cost optimization
Experience with a semantic or metrics layer, such as dbt Semantic Layer/MetricFlow, Cube, or LookML
Track record of standardizing and governing metric definitions
Proficiency with modern BI tools such as Hex, Sigma, Omni, Tableau, Looker, Metabase, or Lightdash
Working proficiency with Python for transformation, tooling, and automation
Strong proficiency with Git and version control practices
Demonstrated fluency with AI-assisted development tools
Experience working with modestly-sized, fast-paced teams
Strong communication skills and ability to partner across engineering, product, and business stakeholders
Working knowledge of iterative, value-focused technical delivery
Candidates must be located within the United States
Prolonged periods sitting at a desk and working on a computer
Must be able to lift up to 15 pounds at times
Professional references may be requested during the hiring process

Benefits

Comp & perks

4-Day Work Week (32-Hour Work Week)
US Remote — Work From Anywhere
Profit Sharing Bonus
3 weeks PTO + Sick Leave + Bereavement
11 paid holidays (not counting ones that fall on a Friday)
401(k) + Match
75% Employer-Paid Health Benefits (Medical, Dental, Vision)
Mental and Physical Wellness Reimbursement ($75/mo each)
$1,000/year travel fund (after 3+ years)
Paid Parental Leave
Dog-Friendly Office
Monthly Social Events
Weekly lunches and snacks for in-office employees