Defining, documenting, and prioritising product metrics and KPIs in close collaboration with Product Managers and senior leadership, ensuring alignment with strategic goals.
Designing and building robust data pipelines to extract product telemetry from our distributed Java-based middleware platform, spanning Lobster-hosted cloud instances and customer-hosted environments (public cloud, private cloud, and on-premises).
Engineering relevant collectors, cleanup & interpolation tasks and data validators.
Architecting and developing the centralised data lake and warehouse infrastructure, selecting and implementing the right technologies to support scalable, reliable analytics based on a variety of data sources.
Creating and maintaining interactive dashboards and reports in Tableau or Microsoft Power BI, tailored to the needs of different stakeholders from C-level to product teams.
Validating and quality-assuring incoming data for plausibility, completeness, and consistency, proactively identifying anomalies and data integrity issues across distributed sources.
Delivering regular analytical reports and ad-hoc insights to senior management and product managers, translating raw data into clear narratives that inform product strategy.
Collaborating with the Power BI specialist and product engineers to establish best practices, documentation, and scalable processes for the analytics function.

3–5 years of experience in a data engineering, analytics engineering, or product analytics role, ideally in a B2B software or SaaS environment.
Strong proficiency in SQL (including stored procedures and views) and experience with at least one programming language for data processing (Python, Java, or similar).
Hands-on experience building and maintaining ETL/ELT data pipelines and working with data warehouse or data lake architectures.
Proficiency with Tableau, Microsoft Power BI and Power Query or a comparable business intelligence tool (Tableau, Looker) for creating dashboards and reports.
Experience with data quality frameworks, the ability to validate, reconcile, and troubleshoot data from distributed and heterogeneous sources.
Understanding of distributed systems and how product telemetry is collected from environments you don’t fully control (cloud, on-premises, hybrid deployments).
Analytical mindset with strong attention to detail and the ability to translate business questions into data requirements.
A clear and efficient communication style in English. German language skills are a plus.

Product Analytics Engineer

Key skills