Analytics Engineer / DWH Engineer - Mid/Senior level

Summary

Join Docplanner as an Analytics Engineer and build a data platform for analytics teams. You will build, automate, and assure the quality of data products, own and improve the DWH data model, and collaborate with analytics teams on building data models for different business areas. The role requires expertise in SQL, Python, data modeling, and experience with dbt and Data Vault. You will act as a product owner and consultant, ensuring platform adoption and success. The position offers a competitive salary, share options, flexible work arrangements, and various benefits.

Requirements

• Extensional experience connected with data warehousing and/or database administration
• Expert in SQL, particularly in query optimization and database design
• Strong skills in Python and SQL , following good coding practices
• Strong data modeling skills (you can name at least five differences between Kimball and Inmon :))
• Deep knowledge of BI, data modeling techniques, and trends (e.g., Data Vault, Kimball, Data Mesh)
• Strong project management skills and experience managing projects end-to-end, ensuring timely delivery and alignment with business goals
• Excellent communication and interpersonal skills
• Growth mindset: nobody ticks all those boxes above, but a willingness to learn is strongly valued here
• Hands-on experience with orchestrators like Airflow* or Dagster
• Ability to work collaboratively and adopt code versioning best practices (git)
• Hands-on experience with cloud technologies and ETL/ELT tools (one among AWS, GPC, Azure, dbt, dagster, airflow, Luigi)
• Good level of English

Responsibilities

• Build, automate and assure the quality of data products in cooperation with analysts and data engineers
• Own and improve the DWH data model, making it more accessible and easier to use
• Own and maintain the DWH cluster
• Apply expertise in dbt, data domainisation, and Data Vault
• Collaborate with analytics teams on building data models for different business areas
• Assure technical guidelines and a big picture view
• Support teams to own their data models and gain autonomy
• Advocate for best practices in data engineering and analytics, ex. by leading workshops and training
• Align data initiatives with business goals
• Proactively communicate with internal stakeholders

Preferred Qualifications

• *Airflow is nice to have, but the must is an orchestrator
• Hands-on experience with dbt in large-scale deployments
• Knowledge of Spark and Scala language are nice to have
• Aligned with our stack (e.g.: AWS ecosystem, Redshift, S3, Tableau, Superset)
• Infrastructure knowledge: Docker, Terraform, Kubernetes, Helm

Benefits

• A salary adequate to your experience and skills
• Share options plan after 6 months of working with us
• Remote or hybrid work model with or hub in Warsaw
• Flexible working hours (fully flexible, as in most cases you only have to be on a couple of meetings weekly)
• 20/26 days of paid time off (depending on your contract)
• Additional paid day off on your birthday or work anniversary (you choose what you want to celebrate)
• Private healthcare plan with Signal Iduna for you and subsidized for your family
• Multisport card co-financing for you to have access to sports facilities across Poland
• Access to iFeel , a technological platform for mental wellness offering online psychological support and counseling
• Free English classes