Who We Are:
Enhesa is the leading provider of regulatory and sustainability intelligence worldwide. As a trusted partner, we empower the global business community with the insight to act today and prepare for tomorrow to create a more sustainable future - positively impacting our environment, our health, our safety, and our future. Navigating the fast-changing compliance and sustainability landscapes, we help them understand not just what they should do (first) but also how to do it. Both in their unique business and anywhere in the world. Now and in the future.
Our Mission:
- Identify EHS requirements for the industry
- Provide EHS compliance tools to companies
- Advise companies in developing and implementing corporate EHS strategies
Enhesa’s core clients include Fortune 500 multinational companies. For more information, visit www.enhesa.com
As part of our highly dynamic team, we offer:
- A competitive salary package & benefits with a flexible home-working policy
- Work/life balance and a fast-paced and driven environment
- Accountability and pride for your projects
Overview of the position
As an Analytics Engineer at Enhesa, you will own the curated (Gold) analytics layer in Microsoft Fabric - turning raw and semi processed data into trusted, well documented dimensional models and metrics for Power Power BI, self service analytics, and AI enabled use cases. This role bridges data engineering and business intelligence by translating ambiguous business needs into scalable analytical data products.
Core responsibilities
- Own the end-to-end Silver-to-Gold transformation layer—clarify requirements, define grains and KPIs, implement business logic, and deliver curated datasets to production.
- Develop performant SQL and PySpark transformations (CTEs, window functions, MERGE/upserts) with incremental processing, idempotency, and recovery patterns.
- Design dimensional models (facts/dimensions, SCD Type 1/2, conformed dimensions) with clearly defined semantics for consistent reporting across domains.
- Optimize Gold schemas for Power BI semantic models and ad hoc analytics—reducing downstream DAX/SQL complexity and enabling scalable self-service.
- Implement quality and trust controls: validation and reconciliation checks, automated tests, documentation and lineage, and monitoring for data freshness and breaking changes.
- Partner with Data Engineers and BI Engineers to align ingestion with consumption; maintain medallion-layer hygiene (partitioning, file sizing, OPTIMIZE/VORDER, schema evolution) in Microsoft Fabric.
- Apply strong engineering practices and governance: Git branching, CI/CD checks, environment promotions, runbooks; secure access patterns (RLS/OLS), least privilege, and data classification.
- Manage stakeholders proactively—surface risks, negotiate scope/timelines, and communicate trade offs and impact clearly.
Education Level
Bachelor’s degree in Engineering, Computer Science, Information Technology, or a related field (or equivalent practical experience).
Experience
3+ years in Analytics Engineering, Data Engineering, or Business Intelligence, with hands-on delivery of production analytical data models and curated datasets consumed by reporting and/or self-service analytics.
Required Technical Skills
- Advanced SQL: CTEs, window functions, query performance tuning, and reusable transformation logic.
- Dimensional modeling: star schemas, OBTs, fact grain definition, SCD Type 1/2, conformed dimensions, and analytics-ready denormalized patterns experience.
- Spark & Delta Lake: performant transformations (joins, partitioning, skew handling); lakehouse and medallion architecture; Delta features (MERGE, OPTIMIZE, ZORDER, time travel, schema evolution).
- Semantic layer awareness (Power BI): models tables and measures for performant semantic models; collaborates to reduce downstream complexity and align KPI definitions.
- Analytics mindset: translates business questions into metrics and data models; strong understanding of KPI definitions, edge cases, and how definitions impact decisions.
- Data quality & observability: defines checks (completeness/validity/reconciliation), monitors freshness, and troubleshoots data issues through root-cause analysis.
- Data access & governance: implements least-privilege access patterns, RLS/OLS concepts, sensitivity/classification expectations, and safe handling of confidential/PII data.
Nice-to-have Technical Skills:
- Transformation frameworks: dbt (models, tests, documentation) or equivalent patterns.
- Orchestration: experience with Fabric or Azure Data Factory pipelines and dependency management.
- Engineering practices: Git and CI/CD workflows, automated testing and documentation standards.
- Microsoft Fabric: Fabric artifacts, capacities, and Fabric-specific optimizations (VORDER).
- Python: scripting for data utilities, profiling, and automation.
Other Required Skills:
- Communication: explains data semantics to non-technical audiences; surfaces scope/timeline/tech-debt risks early.
- Stakeholder partnership: negotiates constructively; balances competing requests; educates business users without condescension.
- Ownership & autonomy: you build, you own it; anticipates downstream impact on consumers.
- Problem solving depth: decomposes complexity; weighs trade offs; digs for root cause rather than patching symptoms.
- Champion of continuous improvement;
- Language: fluent in English.
If you are ready to join our journey, please apply!
Equal Opportunity Employer
Enhesa is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other legally protected characteristic.
Skills Required
- 3+ years in Analytics Engineering, Data Engineering, or Business Intelligence
- Bachelor's degree in Engineering, Computer Science, Information Technology, or a related field
- Advanced SQL
- Dimensional modeling experience
- Spark & Delta Lake experience
What We Do
Enhesa is partner to multi-national corporations that want to help make the world a better place. Our comprehensive EHS and product compliance support empowers our clients to be relevant and resolute in taking care of the environment, health and safety of their collective - globally and locally. Over the past 25 years, Enhesa has built an extensive knowledgebase of EHS and product regulatory content in more than 300 jurisdictions with support in 30+ languages. Combining advanced expertise with the latest AI-powered technology, our team of 75 in-house legal experts translate complex regulatory data into clear requirements. With our standardized, centralized regulatory content, organizations can achieve seamless compliance across their complete business scope - from how they operate to what they create. In 2020 Chemical Watch - the leading global provider of independent intelligence and insight for product safety professionals managing chemicals - was acquired. Their insight helps businesses create safer products and stay ahead of the dynamic chemicals management agenda. In 2021 Scivera – helping leading product brands across the globe to create better products via better chemicals – was acquired. They are driving the transformation towards safer chemistry and material health – and help businesses to simplify the start of their chemical management program. Also in 2021, HCB was acquired - publishing key insights on the global transport, handling and storage of dangerous goods. It is our mission to help build a safer, more sustainable world. We help companies transform their product and operational compliance management. We want you to stay on top of emerging and evolving regulations, fully in the know of what compliance means now and how it will change in the future. We help you comply with confidence – today, tomorrow, across the globe.
