Description

Key Responsibilities

Support data pipeline development and migration from legacy data warehouses to Azure Fabric Lakehouse/Warehouse.

Write efficient SQL queries (T‑SQL preferred) for extraction, transformation, and validation across multiple databases (SQL Server 2022, Azure SQL MI, Synapse).

Develop and debug Python scripts for automation, ingestion, and data quality checks.

Assist in building Fabric dataflows, pipelines, and lakehouse tables aligned with enterprise data‑modeling standards.

Collaborate with senior engineers on ETL design, optimization, and performance tuning.

Perform unit testing, peer code reviews, and maintain documentation in Confluence/Git.

Monitor and troubleshoot data load processes, resolving job failures and updating JIRA/Zephyr test cases.

Continuously learn and apply emerging Azure technologies (Databricks, Fabric, Power BI) to improve processes.

Required Skills & Qualifications

Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field.

7–9 years of professional experience in data engineering.

Strong proficiency in SQL (T‑SQL preferred).

Hands‑on experience with Python scripting.

Solid understanding of data warehousing concepts (ETL, staging, fact/dimension modeling).

Strong expertise with Azure services: Data Factory, Synapse (Fabric experience a plus).

Experience with Git/Azure DevOps, Confluence, JIRA.

Knowledge of data modeling, metadata management, and data quality principles.

Familiarity with Agile/Scrum environments.

Exposure to Power BI and basic DAX concepts.

Strong analytical mindset, attention to detail, and enthusiasm for learning enterprise‑scale systems

Key Skills

Education

Bachelor's degree