Middle Data Engineer — Snowflake / dbt / Azure

Responsibilities: — Build and support production data pipelines using Snowflake, SQL, dbt, and Azure. — Perform hourly ingestion from SQL Server and 24/7 OLTP systems. — Ingest files from customer NAS shares and APIs into Azure Blob Storage. — Build and maintain dbt models in Snowflake. — Handle production issues such as schema changes, failed hooks, missing files, and jobs that fail halfway. Requirements: — At least 2 years of experience in data engineering. — Hands-on experience with Snowflake features including streams, Time Travel, data sharing, and various table types. — Advanced SQL skills; live coding in Snowflake is part of the interview. — Experience with dbt including macros, pre- and post-hooks, and SCD Type 2. — Experience with Azure Data Factory or Azure Synapse Pipelines, including self-hosted integration runtimes. — Proficiency in Python and PySpark. — Familiarity with Git, pull-request workflows, code review, and automated testing. Nice to have: — Experience with Azure Function Apps and Logic Apps. — Knowledge of Microsoft Defender for scanning incoming files. — Experience with Databricks. — Familiarity with orchestration tools such as Airflow. Benefits: — Fully remote work. — Performance-based bonus. — Opportunities for professional growth. Hiring Process: 1. Online coding assessment. 2. Technical interview. 3. Final discussion with the manager. Note: AI tools and outside help are not allowed during interviews. Sessions are recorded.