Core Skills

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.

If you are a results-oriented professional with a passion for data engineering and Azure technologies, we encourage you to apply and join our team.

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

Education