Senior Analytics Engineer (m/f/d)

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.

About AutoScout24

A career driven by you.

Join AutoScout24 Group and experience life in the fast lane. We’re not just leading the market; we’re creating it. We’re constantly innovating, evolving and transforming things for our customers. We’re driven, ambitious and determined to do our best work, together. For a career that doesn’t stand still, where you can put your ideas in the driving seat and change the way the world moves, join our international community.

Responsibilities

• 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
• 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

Requirements

• 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