Senior Data Engineer

Key Responsibilities

• Design, develop, and maintain data ingestion, transformation, and integration pipelines using Azure Data Factory.
• Ensure seamless integration of data from disparate systems and applications.
• Work extensively with MySQL databases for data extraction, transformation, and performance tuning.
• Develop and maintain data lakes and data warehouses on Azure
• Ensure data quality, integrity, and governance across systems
• Optimize SQL queries, stored procedures, and indexing in MySQL
• Collaborate with data scientists, analysts, and business teams to deliver data solutions
• Monitor, troubleshoot, and improve pipeline performance and reliability.

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Technical Skills

Required Skills and Experience

• 6–8 years of experience in data engineering or related roles
• Strong hands-on experience with:
• Azure Data Factory (ADF)
• Azure Data Lake Storage (ADLS Gen2)
• Solid experience with MySQL:
• Query optimization
• Stored procedures
• Indexing and performance tuning
• Proficiency in SQL & PLSQL
• Experience in building data pipelines and data warehousing solutions
• Data quality evaluation and data migration techniques
• Familiarity with REST APIs and data integration techniques
• Experience with version control (Git) and CI/CD practices.
• Understanding of data quality tools and techniques.
• Knowledge of modern data architectures, including Medallion (Bronze/Silver/Gold) design patterns.
  

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Soft Skills

• Excellent communication and collaboration skills to work effectively with cross-functional teams.
• Strong analytical and problem-solving abilities.
• Ability to manage time effectively and deliver in dynamic, fast-paced environments.

Minimum Qualifications

• 6 to 8 years of experience in data engineering, with a focus on cloud-based architecture.
• Proven expertise in SQL, PLSQL & Azure data ecosystem.
• Strong documentation and reporting abilities.

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Preferred Qualifications

• Experience in process modeling and continuous improvement.
• Familiarity with data governance frameworks.
• Domain experience in supply chain management, logistics, or finance analytics, enabling data-driven decision-making across the enterprise.