Data Engineering

Job Description

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