Data Engineer

Must Skills:Microsoft Fabric (hands-on exposure)
Azure Data Lake Storage (ADLS)
Dimensional Modeling (Star Schema)
Power BI / DAX
Medallion Architecture (Bronze/Silver/Gold)
AI tools / automation in data engineering
Scala / advanced Python scripting
Databricks
SQL
Python
ETL
Skill Breakdown:Skill 1: 7+ Years – Data Engineering, Databricks, SQL, Python
Skill 2: 7+ Years – SQL, Microsoft Fabric, Azure Data Factory
Skill 3: 5+ Years – Overall IT Experience


Role Overview:Build, maintain, and optimize scalable data pipelines
Develop data models and analytics layers for reporting
Modernize legacy pipelines using standardized architecture
Collaborate with business stakeholders for requirement gathering
Perform root cause analysis and data validation
Improve system efficiency, reusability, and performance
Leverage AI tools to enhance engineering productivity


Technical Expectations:Strong SQL (performance tuning & optimization)
Experience with Databricks, Azure Data Stack, ADLS
Knowledge of Data Warehousing & Data Lake concepts
Understanding of dimensional modeling & semantic layers
Familiarity with Python/Scala for pipeline development
Exposure to Power BI and downstream analytics


Experience Required:2–4 years of Data Engineering experience
Hands-on experience with cloud-based data platforms
Experience in data pipeline design and troubleshooting
Strong stakeholder communication skills