Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
SQL
BigQuery
dbt
Dagster
Where the posting names them
- Expert in designing modular and performance-optimized analytical data models, and building scalable incremental transformations
- Advanced SQL mastery and extensive native experience within cloud-based big data platforms (e.g. Google BigQuery)
- Practical working familiarity with modern workflow orchestrators like Dagster to synchronize data assets and event-driven pipeline schedules
While operating within an existing ecosystem, the architectural transition from a single monolith into four specialized product teams provides a highly autonomous, greenfield-like environment where your decisions will directly shape our future state and enable us to multiply our Retail Media revenue.
- Design, build, and maintain production-grade analytical data transformations and metrics definitions within Google BigQuery to enable robust performance and budget reporting for our bidding marketplaces
- Establish rigorous, automated data validation frameworks and schema checks to shield public-facing reporting dashboards and analytical tables from upstream variance or structural drift
Nice To Have:
- Data Transformation Tooling: Practical, hands-on experience utilizing dbt (Data Build Tool) for managing version-controlled analytical modeling codebases, validation schemas, and deployment workflows
- Domain Expertise: Prior experience working within an eCommerce, retail tech, or ad-tech ecosystem, with a solid understanding of web analytics tracking, funnel parameters, or ad performance metrics
- Advanced SQL mastery and extensive native experience within cloud-based big data platforms (e.g. Google BigQuery)
- Practical working familiarity with modern workflow orchestrators like Dagster to synchronize data assets and event-driven pipeline schedules
- Extensive experience writing declarative data checks, regression validation assertions, and data quality tests to enforce strict metric definition compliance
Yes. We’ve followed one other Senior Analytics Engineer - Brand Analytics job there since October 2026. It is still up.
HamburgStill up after 28 days, first seen Oct 8
This jobUp 28 days so far, first seen Oct 8
Oct 8Today
Demand for Analytics Engineer roles
New Analytics Engineer postings at the employers we follow are down 9% over the last 5 weeks compared with the 5 before.
August 17Last week
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Analytics Engineer, by the work the posting describes.
Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.
Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.
A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.
US government figures for database architects
Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs
The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.
The Brand Analytics team is the insights engine: its mission is to empower data-driven decision-making for Retail Media Partners by providing a single source of truth. This creates a powerful opportunity for brands to gain deep performance visibility and turn enterprise-scale data into actionable growth strategies.
While operating within an existing ecosystem, the architectural transition from a single monolith into four specialized product teams provides a highly autonomous, greenfield-like environment where your decisions will directly shape our future state and enable us to multiply our Retail Media revenue.
Design, build, and maintain production-grade analytical data transformations and metrics definitions within Google BigQuery to enable robust performance and budget reporting for our bidding marketplaces
Establish rigorous, automated data validation frameworks and schema checks to shield public-facing reporting dashboards and analytical tables from upstream variance or structural drift
Lead the migration of complex analytical transformation rules and data aggregation queries directly out of historical legacy application repositories into modular, decoupled analytics environments
Partner with Data Engineers to engineer clean data modeling boundaries around shared catalog assets (such as products and brands) that connect the decentralized product stack with core platform endpoints
Set analytics engineering standards, direct code-reuse conventions, and establish reusable data blueprints within the team
Qualifications
Expert in designing modular and performance-optimized analytical data models, and building scalable incremental transformations
Advanced SQL mastery and extensive native experience within cloud-based big data platforms (e.g. Google BigQuery)
Practical working familiarity with modern workflow orchestrators like Dagster to synchronize data assets and event-driven pipeline schedules
Extensive experience writing declarative data checks, regression validation assertions, and data quality tests to enforce strict metric definition compliance
Proficiency with Git version control, structured code review flows, and automated deployment infrastructure like GitLab CI/CD pipelines
A structural developer who excels at transforming loose business descriptions into highly structured, reliable, and standardized metrics environments
Able to cleanly convey complex database schemas, transformation choices, and analytical definitions to software developers
Highly driven to establish data blueprints within a technical greenfield context
Nice To Have:
Data Transformation Tooling: Practical, hands-on experience utilizing dbt (Data Build Tool) for managing version-controlled analytical modeling codebases, validation schemas, and deployment workflows
Domain Expertise: Prior experience working within an eCommerce, retail tech, or ad-tech ecosystem, with a solid understanding of web analytics tracking, funnel parameters, or ad performance metrics
Simply apply online via our career page - we will get back to you as soon as possible!
A Place Where You Can Be You
We take it as our responsibility to create an environment where everyone feels welcome, exactly as they are.
Different backgrounds and perspectives make us stronger and shape our culture in ways that matter.
What we stand for internally, we stand for as a brand: acceptance, inclusion, and a fairer approach to fashion.
Company Description
ABOUT YOU is one of Europe’s fastest growing e-commerce companies. Based in Hamburg and Berlin, we operate at the intersection of fashion and technology. Our mission is to rethink online shopping and make it personal and seamless. This takes more than good ideas. It takes people who take initiative and challenge the status quo. We believe in flat hierarchies, direct communication, and pragmatic decisions. No long approval chains. Just ownership, trust, and clear responsibility. We work hard, but we also believe in enjoying the ride together - over team lunches, afterwork drinks, company events, or a quick coffee in between meetings. If this sounds like you, ABOUT YOU could be the right place to bring in your perspective.