(Senior) Data Engineer
As a Data Engineer, you are in charge of our data warehouse and data pipelines. To support our stakeholders in the creation of specialized dashboards and reports, you manage a diverse set of data sources by utilizing different ETL platforms and building custom connectors. Your mission is to enable our team to make decisions with a 360-degree view of our business and user. In your role you work closely with your stakeholders and manage your own data engineering roadmap.
HOW WE WORK:
Our Highsnobiety Tech/Product organization consists of 3 interdisciplinary and self-organized teams with a total of 10+ dedicated employees. Scrum and Kanban are our methods of choice for a transparent and open product management. Every team is continuously delivering software and is closely collaborating with their stakeholders. We organize regular product demos to share our progress, and Hack days to innovate our products. For a transparent and well balanced work culture, the entire department shares their feedback with each other in a monthly retrospective to celebrate successes and to improve methods.
We serve both internal and external users and believe in high standards when building our products. To ensure quality, we apply code reviews, extreme programming methods and test coverage tracking. Also, we follow a “you build it – you run it” approach and deploy our services on Google Cloud Platform using Docker and Kubernetes.
As technology moves fast, it’s key for us to invest in our employees’ growth. We provide access to the best learning platforms, we run tech workshops, organize regular pair-programming sessions with senior developers and we also sponsor conference visits. Scrum is our method of choice for a transparent, open and self-organized product and project management.
- Identify opportunities for leveraging audience and business data in collaboration with the Commerce, Audience Development and Product teams
- Define relevant KPIs & implement required tracking to derive analytical insights for different departments
- Evolve existing dashboards & reporting capabilities
- Grow our data warehouse (BigQuery) and BI environment (Looker) by connecting a wide range of data sources (via Airflow)
- 3+ years relevant experience in a data science, data engineering or back-end engineering role
- Experience in building and maintaining ETL / ELT pipelines (e.g. Airflow, dbt)
- Experience in operating multiple databases/data warehouses
- Strong knowledge of SQL, relational database systems (e.g. PostgreSQL), column-based databases (e.g. BigQuery) and stream based systems (e.g. Kafka)
- Solid working knowledge of Python
- Knowledge of Ruby, Elixir or R is a plus
- Development experience in dbt and Looker (LookML) is a big plus
- Ability to synthesize data from multiple sources and visualize it effectively
- Strong analytical and problem-solving skills
- Experience with E-Commerce and/or publishing/social media data is a big plus
- Strong communication and interpersonal skills
- Proactive, creative & self-starter attitude
WHAT WE OFFER:
- Support and mentoring by the core platform development team
- Broad spectrum of technological challenges
- Freedom to experiment and work with cutting edge technologies
- Pair programming, hack days, internal talks, growth budget and conference visits
- The unique entrepreneurial opportunity to pro-actively shape a company and help build a global brand
- A bright and spacious Design office, which reflects our brand and focuses on employee well-being, located in the upcoming and vibrant district of Schöneberg.
- Motivating, international and creative work atmosphere
- High degree of responsibility
- Competitive compensation (incl. visa/relocation support)
- Attractive employee benefits (e.g. company events, various discounts)
More information on our tech stack: https://stackshare.io/highsnobiety
Highsnobiety is a global community of independent-minded creatives & professionals: Every perspective matters. That’s why we’re proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, ethnicity, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression or genetic information.