Description :

- Develop and maintain robust ETL/ELT pipelines using tools such as Apache PySpark, Airflow, and SQL

- Design and optimize data models for both structured and unstructured data

- Collaborate with Application, Digital Product, and Technology teams, as well as analysts and software engineers, to deliver high-quality data solutions

- Ensure data quality, integrity, and security across all systems

- Implement data governance, privacy, and compliance standards

- Monitor, troubleshoot, and optimize data pipeline performance and reliability

Required Skills :

- Proficiency in SQL, Python, and Apache Spark

- Hands-on experience with AWS cloud services (e.g., S3, Redshift, Airflow, Lambda, EMR , EC2, kinesis)

- Familiarity with big data and RDBMS technologies such as Hadoop, Spark, Kafka

- Strong understanding of data warehousing concepts, especially Amazon Redshift

- Experience with CI/CD pipelines and version control tools (Bitbucket, Git, Jenkins)

Functional Skills :

- In-depth understanding of Asset Management Companies (AMCs) and Capital Markets

- Familiarity with business processes across Sales, Finance, and Investment domains

- Strong grasp of how investor-level (360) data is derived from scheme-level data points