Azure Data Engineer

Exp: 5 - 10 Yrs

Location: Hyderabad, Bangalore, Pune, Chennai and Gurgaon

Skills: Python, Pyspark, SQL, Databricks, Unity catalog, Azure Datafactory, Azure Synapse, ETL, Orchestration, Migration and Medallion Architecture

As a Databricks Data Engineer, you will play a crucial role in designing, developing, and optimizing data processing pipelines on the Databricks platform. You will be responsible for transforming raw data into actionable insights and enabling data-driven decision-making across the organization. Your expertise in data engineering and proficiency with the Databricks environment will be essential in building scalable and efficient data workflows.

Key Responsibilities:

• Develop and maintain data pipelines using Databricks, Spark, and other data processing technologies.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and ensure data quality and accessibility.
• Implement and optimize ETL processes to support analytics and reporting initiatives.
• Monitor and troubleshoot data pipeline performance, ensuring timely delivery and reliability.
• Contribute to the design and implementation of data architecture and data models.
• Utilize Databricks notebooks for data exploration, visualization, and sharing insights with team members.
• Stay updated with the latest trends and advancements in data engineering and the Databricks platform.

Skills and Tools Required:

• Proficiency in Databricks and Apache Spark.
• Strong programming skills in Python or Scala for data processing.
• Experience with ETL processes and tools.
• Knowledge of data modeling and data warehousing concepts.
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
• Experience with SQL and database technologies (e.g., MySQL, PostgreSQL, or others).
• Familiarity with data visualization tools (e.g., Tableau, Power BI) is a plus.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills to work effectively within a team.