Senior Data Engineer

As an ETL Developer, you will be responsible for designing, building, and maintaining ETL pipelines using MSBI stack, Azure Data Factory (ADF) and Fabric. You will work closely with data engineers, analysts, and other stakeholders to ensure data is accessible, reliable, and processed efficiently.

Key Responsibilities:

• Design, develop, and deploy ETL pipelines using ADF and Fabric.
• Collaborate with data engineers and analysts to understand data requirements and translate them into efficient ETL processes.
• Optimize data pipelines for performance, scalability, and robustness.
• Integrate data from various sources, including S3, relational databases, and APIs.
• Implement data validation and error handling mechanisms to ensure data quality.
• Monitor and troubleshoot ETL jobs to ensure data accuracy and pipeline reliability.
• Maintain and update existing data pipelines as data sources and requirements evolve.
• Document ETL processes, data models, and pipeline configurations.

Qualifications:

• Experience:

  3+ years of experience in ETL development, with a focus on ADF, MSBI stack, SQL, Power BI, Fabric.

• Technical Skills:

• Strong expertise in ADF, MSBI stack, SQL, Power BI.
• Proficiency in programming languages such as Python or Scala.
• Hands-on experience with ADF, Fabric, Power BI, MSBI.
• Solid understanding of data warehousing concepts, data modeling, and ETL best practices.
• Familiarity with orchestration tools like Apache Airflow is a plus.

• Data Integration:

  Experience with integrating data from diverse sources, including relational databases, APIs, and flat files.

• Problem-Solving:

  Strong analytical and problem-solving skills with the ability to troubleshoot complex ETL issues.

• Communication:

  Excellent communication skills, with the ability to work collaboratively with cross-functional teams.

• Education:

  Bachelor's degree in computer science, Engineering, or a related field, or equivalent work experience.

Nice to Have:

• Experience with data lakes and big data processing.
• Knowledge of data governance and security practices in a cloud environment.