Starschema is looking for a Data Pipeline engineer to join its team on an Enterprise Data Platform project. You will create data pipelines based on various datasets and data sources, implementing SQL logic into dbt config files and supervising the deployment process of your software module integrations. The work is collaborative within a multi-team environment, using technologies like SQL, Git, Snowflake, dbt and Airflow, with occasional Python.
Responsibilities
- ▹Communicate with management about business requirements
- ▹Implement SQL logic into dbt config files based on the provided data model
- ▹Test data models and debug dbt and Airflow logs
- ▹Take part in daily stand-ups, grooming sessions and plannings
- ▹Deploy pipeline elements/configs into DEV/pre-PROD/PROD environments
Requirements
- ▹3-5 years of experience
- ▹Knowledge of SQL
- ▹Excellent English communication skills
- ▹Excellent problem-solving skills
Nice to have
- ▹Experience with Snowflake
- ▹Experience with dbt
- ▹Experience with Airflow
- ▹Experience with Git or other version control systems
- ▹Experience with CI/CD pipelines
Soft skills
What we offer
- ▹Home office: guideline of two days a week in office, untracked and flexible
- ▹Medicover health insurance (with yearly check-ups)
- ▹BKV pass or parking space
- ▹Unlimited Life1 gym pass (any Life1 gym in Budapest) or gym reimbursement in Szeged
- ▹Company mobile subscription (also for personal use)
- ▹Company laptop
- ▹Employee Assistance Program (EAP), available 24/7
- ▹Online English class once a week
- ▹Professional and soft skill trainings
- ▹Referral bonus
- ▹Baby bonus, paternity leave and baby box for newborns
- ▹Lots of fruit in the office, free biweekly massage, online yoga
- ▹Soccer court, hiking community, active social life and community events
- ▹Dog-friendly office
- ▹Birthday holiday - an additional day off
About the company
Starschema believes data has the power to change the world and helps organizations use data to make better business decisions, build smarter products and deliver more value. On this Enterprise Data Platform project, multiple smaller teams work on different parts: a Core Framework team builds the engine while pipeline engineering teams develop data pipelines using the pre-built framework.