Azure Data Engineer (Lead)

Key Responsibilities:

• Design, develop, and implement data ingestion, processing, and reporting pipelines using the Azure Data Engineering stack.
• Lead and mentor a team of data engineers to deliver high-quality solutions.
• Utilize Azure Data Factory, Azure Data Lake Storage Gen2 (ADLS Gen2), and Azure Synapse Analytics for data workflows.
• Develop scripts and data transformation logic using Python and SQL.
• Leverage Databricks and PySpark for big data processing (good to have).
• Collaborate with stakeholders to understand business requirements and translate them into technical solutions.
• Ensure data quality, reliability, and integrity throughout the data lifecycle.
• Optimize and troubleshoot data pipelines for performance and scalability.
• Document technical specifications, processes, and workflows for effective knowledge sharing.
• Qualifications and Requirements:
• 8-10 years of hands-on experience in data engineering, with a strong focus on Azure technologies.
• Proficiency in Azure Data Factory, ADLS Gen2, Azure Synapse Analytics, Python, and SQL.
• Hands-on experience with PySpark and Databricks is highly desirable.
• Proven experience in leading teams and managing technical delivery.
• Strong understanding of data modeling, ETL/ELT processes, and pipeline orchestration.
• Experience in implementing end-to-end data solutions, from ingestion to reporting.
• Excellent problem-solving skills and the ability to troubleshoot complex issues.
• Strong communication skills with the ability to convey technical concepts to non-technical stakeholders.
• Bachelors degree in Computer Science, Information Technology, or a related field.

EXPERIENCE

• 11-12 Years

SKILLS

• Primary Skill: Data Engineering
• Sub Skill(s): Data Engineering
• Additional Skill(s): Python, synapse, Azure Data Factory, Azure SQL Development