Snowflake Data Engineer

At Hiflylabs, we are looking to extend our Analytics Engineering team. This team typically works with international clients in small squads, almost exclusively in agile.

We expect you to be a data-oriented person with data/software engineering chops and at least a pinch of business understanding.

You will be building data pipelines in Snowflake, sometimes as a Hiflylabs team member and sometimes more deeply intertwined with the clients’ organization. Depending on the assignment and its phase you will be designing and implementing data ingestions and transformation logics, and sometimes optimize complex ETL processes. You will be working with technical-focused as well as business-oriented colleagues, so you will have the ability to do deeply technical work as well as converse with product managers and end users and see how your work drives the organization forward.

Main Tasks

• Design and implement Data Pipelines in Snowflake
• Develop ingestion pipelines from various sources (via Snowpipe and other means)
• Create data transformations with SQL, Python, PaaS and 3rd party tools (e.g. dbt)
• Optimize existing pipelines and transformations for cost, load time, and maintainability
• Automate data ingestion and transformation (often with Airflow or similar tools)
• Help business users to formulate their needs on the one hand and to make the most of the data platform on the other hand.

Requirements

Requirements

• Working experience with and in-depth knowledge of Snowflake and its family of tools, preferably over multiple projects. As an orientation, you are likely to have 2+ years of hands-on Snowflake experience.
• Data transformation background: sound conceptual understanding and practical experience of data modeling and ETL processing, including extensive knowledge of SQL, including Snowflake’s SQL flavor. As an orientation, you are likely to have 4+ intensive years in the field.
• At least some experience in cloud data management in AWS or GCP data stack components (primarily batch data management, storage, loading, transformation of structured data, Data Lake storage and management tools).
• Team player with ability and explicit willingness to cooperate with other team members, including non-technical business stakeholders in moving the project forward. For this you need to be proactive, and to have some level of business understanding and a genuine interest in the business impact of the project.
• Strong technical and business English (oral, reading and writing).

Advantages

• SnowPro certification, preferably SnowPro Advanced Data Engineer.
• Development background in Python, preferably focused on data ingestion / transformation.
• PySpark / Spark experience.