Senior Analytics Engineering Manager (w/m/d)
Skills
About the role
Join one of the world’s largest and most innovative digital real estate tech companies.
Backed by global investment leaders KKR and CPP Investments, AVIV Group is redefining how people buy, sell, rent, and value property across Europe and the Middle East. With a strong presence in France, Germany, Belgium, and Israel, we’re behind some of the region’s most iconic digital real estate platforms — including SeLoger 🇫🇷, immowelt 🇩🇪, Immoweb 🇧🇪, Meilleurs Agents 🇫🇷 (France’s leading property valuation platform), and Homeday, one of Germany’s fastest-growing proptechs.
Our mission? To simplify life’s most valuable transactions. We bring together data, technology, and human insight to empower millions of people to unlock their perfect place!
Job Description
About the role
We're looking for a Senior Analytics Engineering Manager to lead one of our analytics engineering functions at the intersection of data infrastructure and business intelligence. You'll own the data models, pipelines, and semantic layer that power decisions.
What you'll do
Lead and grow a team of analytics engineers (ICs and potentially tech leads), providing mentorship, technical direction, and career development.
Own the design and governance of the company's core data models — including customer, order, product, inventory, and marketing attribution domains.
Define and enforce standards for dbt project structure, testing, documentation, and code review across the analytics engineering team.
Drive adoption of a semantic layer or metrics layer to enable consistent KPI definitions across all reporting surfaces.
Collaborate with stakeholders in merchandising, marketing, finance, and operations to translate business requirements into robust data models.
Establish and track SLAs for data freshness, accuracy, and pipeline reliability; lead incident response when data quality issues arise.
Evaluate and evolve the modern data stack (warehouse, transformation, orchestration, BI) as business needs change.
Represent analytics engineering in cross-functional planning, roadmapping, and executive stakeholder conversations.
Qualifications
What we're looking for
5–8 years of experience in analytics engineering, data engineering, or a closely related field, with at least 2–3 years in a people management role.
Deep expertise with dbt (dbt Core or dbt Cloud) — including advanced modeling patterns, macros, testing, and documentation best practices.
Strong SQL skills and fluency with a cloud data warehouse (Snowflake, BigQuery, or Databricks preferred).
Proven experience in e-commerce or retail data domains — orders, returns, inventory, customer lifetime value, product performance, digital funnels.
Track record of building high-trust data products: well-documented, tested, and adopted by stakeholders across the business.
Experience managing stakeholder relationships and translating ambiguous business questions into clearly scoped data work.
Strong written and verbal communication skills; ability to convey technical concepts to non-technical audiences.
Nice to have
Experience implementing or operating a semantic/metrics layer (e.g. dbt Semantic Layer, Cube, MetricFlow).
Familiarity with real-time or near-real-time data pipelines for retail use cases (inventory sync, price updates, etc.).
Exposure to ML feature engineering or working alongside data science teams on shared data infrastructure.
Experience with BI tools such as Looker, Tableau, or Metabase, and understanding of how modeling choices affect reporting performance.
Additional Information
Questions about this role
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