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Analytics Engineer
GoodHabitz. Assess the Databricks estate, define trust levels, and propose owners for each source and table .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in SQL and dimensional modelling to build and manage data transformations and governance processes. Capable of collaborating with cross-functional teams to ensure data quality and effective measurement strategies.
Highest-signal resume keywords
Production-Level SQL ExperienceDimensional ModellingEvent Taxonomy DevelopmentData Governance ProcessesDatabricks/Unity Catalog Experience
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
SQLDimensional ModellingSemantic LayersData ContractsCI ValidationDefinition of Done GatesData Quality StandardsTracking Plan DevelopmentReusable Model DesignMeasurement Definition
Soft Skills
CollaborationProblem-SolvingCommunication
Tools & Technologies
DatabricksUnity CatalogB2B SaaS ProductsData Observability ToolingGit
Industry Keywords
Data GovernanceEvent TaxonomyProduct MeasurementSelf-Service AnalyticsData Quality
Tech Stack
Tools & technologiesSQLUnity
About the role
Key responsibilities & impact- Assess the Databricks estate, define trust levels, and propose owners for each source and table
- Build and version silver-to-gold dbt transformations using dimensional modelling and a semantic layer
- Design point-in-time dimensions that preserve history
- Design and roll out an event taxonomy and naming convention with engineering
- Own the metric catalog and sign-off process
- Build activation, engagement, and retention models
- Build semantic models and documentation for self-service analytics
- Set data quality standards and incorporate sign-off into a Definition of Done gate
- Monitor instrumentation to identify issues early
- Partner with product teams so measurement informs feature development
- Collaborate with the data engineer, product stakeholders, business stakeholders, PMs, designers, and engineers
- Report to the Product Data Lead
Requirements
What you’ll need- Production-level experience with SQL
- Git as a working habit
- Experience with dimensional modelling and semantic layers
- Experience building a tracking plan or event taxonomy in partnership with engineering
- Track record of building enforcement processes such as data contracts, CI validation or Definition of Done gates
- Ability to translate ambiguous product and business questions into clear, durable measurement definitions
- Experience with Databricks/Unity Catalog, B2B SaaS multi-surface products, or data observability tooling is a plus
- Experience working inside a product team or closely alongside PMs, designers and engineers
- Willingness to build governance and standards from scratch
- Ability to design reusable models across a fragmented data estate
- Comfort defining processes and enforcing standards
Benefits
Comp & perks- Competitive salary and role-specific performance bonus
- Paid time off – 25 days holiday
- Travel budget
- Flexible work environment
- Laptop
- Unlimited access to GoodHabitz resources and MyAcademy
- Mental coaching support
- Diverse and inclusive teams
- Themed events and team-building activities
- Annual fully paid Do-Good Day for volunteer work
- Disability and pension coverage