Gestalte deinen Traumjob als Business Intelligence (BI) Data Engineer bei Haiilo GmbH in Hamburg

What we’re looking for:

• Your background: You should have a minimum of 5 years of experience in data engineering, BI development, or a similar role where you gained expertise in SQL and relational databases like PostgreSQL, MySQL etc.
• Your expertise:
  • Must: You can demonstrate your know-how with data warehousing solutions like BigQuery, Redshift, or Snowflake, have proficiency in ETL tools and frameworks like Apache Airflow, Airbyte, Talend and experience with cloud platforms
  • Must: For our own application we use python scripts with Kubernetes and SQL logic with BigQuery, therefore you should have built experience with that as well as with BI and data visualization tools (e.g., Tableau, Power BI, Looker etc.).
  • Must: Experience in developing and optimizing data transformation workflows using dbt
  • Bonus points:, knowledge of data governance and compliance frameworks (e.g., GDPR) and familiarity with ML concepts
• Your personal skills: You have strong analytical and problem-solving skills with an ability to identify and resolve data-related issues
• Your teamwork abilities: You are a team player, who takes responsibility for what they do and who is able to collaborate in an international environment with excellent communication skills

We encourage you to apply even if your profile does not yet meet all the requirements for the position. At Haiilo we support your personal development as well as your individuality, no matter what background you have.

What you’ll do:

• You are the first point of contact for all BI topics, from architecture to reporting issues and will have an integral role in data in data projects, collaborating with engineers and business stakeholders to gather requirements and deliver data solutions that support business needs
• Design and implement robust, scalable data pipelines to collect, process, and store data from various sources
• Develop and maintain ETL (Extract, Transform, Load) processes to ensure data integrity and availability
• Optimize and maintain data warehouses and databases to ensure high performance and reliability
• Implement and enforce data governance policies and procedures to maintain data quality, consistency, security and compliance
• Create and maintain documentation for data processes, systems architecture, and data models
• Monitor and troubleshoot data pipeline performance, identifying and resolving issues promptly