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# Analytics Engineer

- **Company:** AutoScout24 Nederland B.V.
- **Location:** München, Germany
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Business Analytics Applications, Data Analysis, Cloud Engineering, Information Engineering, Data Governance, Data Infrastructure, Python (Programming Language), SQL Databases, Usage Analysis, Data Processing, Sql Optimization, Technical Debt, Data Layers, Semantic Modeling
- **Published:** November 13, 2026
- **Apply:** https://job-boards.greenhouse.io/autoscout24/jobs/8202620003

## About the Role

* 7+ years of experience in Analytics Engineering, Data Engineering, or a related data role

 * Deep experience designing, building, and scaling analytical models and reusable data products

 * Advanced SQL skills and strong knowledge of dimensional and semantic modeling

 * Strong experience with cloud-native analytical platforms, ideally AWS services such as Glue, Athena, S3, or MWAA

 * Practical Python experience for data processing, automation, validation, or troubleshooting

 * A strong track record of owning complex technical initiatives within a team or across closely related teams

 * Experience setting technical direction, resolving ambiguity, and aligning stakeholders

 * Strong understanding of data quality, testing, observability, documentation, and operational ownership

 * Experience improving modeling standards, development workflows, review practices, or quality gates

 * The ability to influence technical and business stakeholders through clear reasoning and communication

 * Experience mentoring analytics engineers, analysts, or other data practitioners

 * A good understanding of data privacy, security, governance, and compliance in analytical systems

 * Experience with semantic layers, shared metric frameworks, or AI-driven analytics is a strong advantage

 * A proactive, collaborative, and solution-driven mindset

What success looks like

 * You act as a trusted senior technical contributor within the team

 * You own complex workstreams and help the team navigate difficult technical decisions

 * Core models and semantic assets become more scalable, reliable, and reusable

 * Engineering quality improves through stronger standards, reviews, mentoring, and automation

 * Stakeholders trust your technical judgment and involve you early in important decisions

## Description

As a Senior Analytics Engineer, you will be a senior technical contributor within the Analytics Engineering team and help shape the data foundations behind reporting, self-service analytics, and AI-driven decision-making. You will own complex technical workstreams, set direction for team-level analytical systems, and help improve the standards, practices, and architecture used across the team.

What you'll do

 * Own complex analytics engineering workstreams from problem framing through delivery and adoption

 * Design and evolve scalable analytical models, semantic layers, and reusable data products

 * Set technical direction for team-owned models and analytical systems

 * Resolve ambiguity and align stakeholders around clear, pragmatic technical decisions

 * Improve modeling standards, documentation, testing, review practices, and quality gates

 * Drive consistency in KPIs, metrics, and analytical logic

 * Partner with Data Platform, Product Analytics, Engineering, and Data Governance teams

 * Improve the performance, reliability, and cost efficiency of AWS-based analytical workloads

 * Contribute to AI-driven capabilities such as text-to-SQL, semantic modeling for AI, automated insights, and conversational analytics

 * Guide complex refactoring, migrations, and technical debt reduction

 * Review analytical solutions for correctness, maintainability, privacy, security, performance, and business fit

 * Mentor analytics engineers and analysts through reviews, pairing, and technical guidance

 * Turn recurring quality or delivery issues into reusable standards, automation, and documentation

 * Connect technical decisions to product, operational, and business outcomes