Analytics Engineer

Interroll Group; Rho; In loco; EUR 70.000 - 95.000; Tempo pieno

Descrizione del lavoro

Interroll Group in Italy is seeking an Analytics Engineer to own the end‑to‑end data journey from source to insight, building Data Products in Databricks, exposing them via Power BI, and turning findings into decisions.

You will join the Business Management team, working with Sales, Finance and Group IT, implementing scalable data models, governance, and dashboards that support operational teams up to senior management.

Competenze

• 4+ years across data engineering, analytics engineering and BI.
• Strong SQL and Python/PySpark skills.
• Databricks and Lakehouse experience required.
• Power BI proficiency especially semantic models.
• Experience with SAP data sources is a plus.
• Fluent English; German/Italian a plus.

Mansioni

• Design and build data models in Databricks.
• Develop and orchestrate data pipelines from raw sources to curated datasets.
• Integrate data from ERP/CRM into conformed dimensions and facts.
• Implement data governance in Unity Catalog and CI/CD.
• Create Power BI reports and semantic models with DAX and security.
• Define KPIs with stakeholders and support data-driven decisions.

Conoscenze

SQL

Python

Databricks

Power BI

CI/CD

Data product

SAP data

Agile

Business sense

English

German

Italian

Descrizione del lavoro

Interroll is building its enterprise data platform on Databricks, with SAP S/4HANA, SAP Sales Cloud and other business systems as core sources, organised around Data Products: curated, governed datasets with clear ownership, defined consumers and a published contract.

We are looking for an Analytics Engineer to own the full journey from source data to insight: designing and building Data Products in Databricks, exposing them through Power BI, and turning them into analysis that drives decisions.

You will join the Business Management team, working with stakeholders across Sales, Finance and other business functions, and with Group IT, which runs the platform and source system integration.

What you will do

Data engineering and modelling

• Design and build scalable data models in Databricks (SQL, PySpark, Delta Lake) using a layered architecture (for example, medallion).
• Develop and orchestrate reliable pipelines, from raw source extracts to curated, analysis-ready datasets.
• Integrate and harmonise data from ERP, CRM and other systems into conformed dimensions and facts.
• Put complex business logic into reusable, tested and documented code, with data quality checks and reconciliation against the source systems.
• Manage governance in Unity Catalog (access control, lineage, documentation) and apply engineering best practices: version control, code review and CI/CD.

Power BI and analytics

• Connect Databricks to Power BI (Databricks SQL warehouses, import, DirectQuery) and design reporting tables that perform well in Power BI.
• Build and maintain shared Power BI semantic models: DAX measures, row-level security, incremental refresh and performance tuning.
• Build dashboards for audiences from operational teams up to senior management.
• Carry out recurring and ad-hoc analysis, and turn findings into clear, actionable recommendations.
• Define and standardise KPIs with business stakeholders, so every function works from one version of the truth.

Data products

• Own Data Products end to end: define their purpose, consumers, scope and success metrics, then deliver, monitor and evolve them.
• Gather and prioritise requirements from business users, and manage the product backlog and roadmap.
• Define and enforce data contracts (schema, business definitions, quality rules, refresh SLAs) through automated testing and monitoring.
• Drive adoption: publish certified Power BI semantic models and catalogue documentation, onboard users, collect feedback and track usage.
• Manage versioning and the product lifecycle so downstream consumers are never surprised by a breaking change.
• Agree source data requirements and integration patterns with IT.

What you bring

• 4+ years across data engineering, analytics engineering and BI, with hands‑on experience at both the model and the report level.
• Expert SQL and solid Python/PySpark.
• Hands‑on Databricks experience (Delta Lake, Unity Catalog, Workflows/Jobs), or a similar lakehouse platform (must have).
• Advanced Power BI (strong plus): semantic model design, DAX, row‑level security, refresh and performance optimisation, and connecting to Databricks.
• Experience with testing and CI/CD for data (for example, Databricks Asset Bundles, dbt, Azure DevOps or GitHub Actions).
• Understanding of Data Product and data mesh principles. Experience in product ownership for data or analytics products is a strong plus.
• Experience with SAP data (S/4HANA CDS views, SAP Datasphere, CRM) is a strong plus.
• Experience in agile, product‑oriented teams with a backlog and roadmap.
• Business sense and the ability to explain complex findings to non‑technical audiences.
• Fluent English. German and/or Italian are an advantage.

Why Interroll

• Help build the company’s data platform from the start, with real influence over how it is designed.
• Close collaboration with management: your work feeds decisions across the business.
• A global industrial leader in material handling, with an international team and room to grow.