FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Senior Enterprise Analytics Engineer – Commercial
AutoStore™. Build and maintain Silver and Gold-layer data products for the Commercial domain in Databricks .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and maintaining Silver and Gold-layer data products, translating business requirements into scalable data solutions, and ensuring data quality and governance. Proficient in advanced SQL, analytics engineering, and modern cloud data platforms to support advanced analytics and GenAI use cases.
Highest-signal resume keywords
Advanced SQL SkillsAnalytics EngineeringData GovernanceDatabricksEnterprise Analytical Data Models
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data ModellingComplex TransformationsQuery OptimisationDimensional ModellingSemantic ModellingData QualityData LineageData DocumentationBI Issue InvestigationSustainable Data Solutions
Soft Skills
CollaborationStakeholder EngagementProblem Solving
Tools & Technologies
DatabricksSnowflakeBigQueryMicrosoft FabricPySparkDbtPython
Industry Keywords
Commercial DataCRMSales DataMarketing DataCustomer Data
Tech Stack
Tools & technologiesBigQueryCloudPySparkPythonSQL
About the role
Key responsibilities & impact- Build and maintain Silver and Gold-layer data products for the Commercial domain in Databricks
- Turn enterprise data into reliable, reusable models, metrics, and datasets for reporting and analytics
- Work with Commercial stakeholders to understand business needs and define KPIs and analytical solutions
- Partner with the IT Data team to align data products with enterprise platforms, architecture, pipelines, and engineering standards
- Own data quality, documentation, lineage, and governance for key Commercial datasets and metrics
- Investigate data and BI issues across source systems, transformation layers, and reporting
- Replace recurring manual fixes with sustainable data-model or transformation improvements
- Establish analytics engineering standards and AI-ready data foundations
- Support future advanced analytics and GenAI use cases
Requirements
What you’ll need- 7+ years of experience across Analytics Engineering, Data Engineering, Business Intelligence, or related areas
- Hands-on technical experience
- Experience designing and building enterprise analytical data models, Silver/Gold data layers, and reusable datasets
- Advanced SQL skills, including complex transformations, data modelling, query optimisation, and troubleshooting across different data sources and layers
- Experience with dimensional and semantic modelling
- Experience with modern cloud data platforms such as Databricks, Snowflake, BigQuery, or Microsoft Fabric
- Experience translating business requirements into scalable data solutions
- Experience working directly with business stakeholders and closely with Data Engineering, BI, and Analytics teams
- Experience with PySpark, dbt, Python, data governance/cataloguing, or CI/CD is an advantage
- Experience working with commercial data such as CRM, sales, marketing, or customer data is valuable
Benefits
Comp & perks- Health insurance
- Generous pension plan
- Mental and physical well-being support
- Structured onboarding plan
- Career opportunities within the company
- Collaborative and inclusive culture
- International and supportive environment