Data Engineering

Required Qualifications:

• Experience:
• 6-8 years of total experience in data engineering, with 3+ years of hands-on experience in Databricks, PySpark, and AWS.
• 3+ years of experience in Python and SQL for data engineering tasks.
• Experience working with cloud ETL services such as AWS Glue, GCP DataProc/DataFlow, Azure ADF and ADLF.
• Technical Skills:
• Strong proficiency in PySpark for large-scale data processing and transformation.
• Expertise in SQL, including window functions, for data manipulation and querying.
• Experience with cloud-based ETL tools (AWS Glue, GCP DataFlow, Azure ADF) and understanding of their integration with cloud data platforms.
• Deep understanding of data schemas and models used across various business contexts.
• Familiarity with data warehousing optimization techniques, including partitioning, indexing, and query optimization.
• Knowledge of data security best practices (e.g., encryption, access control, and compliance).
• Agile Methodologies: Experience working in Agile (Scrum or Kanban) teams for iterative development and delivery.
• Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.

Skills

Python,Databricks,Pyspark,Sql

Job Type: Full-time

Pay: ₹1,500,000.00 - ₹2,100,000.00 per year

Experience:

• Data Engineering: 6 years (Required)
• Databricks: 3 years (Required)
• Pyspark: 3 years (Required)
• AWS: 3 years (Required)

Work Location: In person