Description

You will lead large-scale data transformation initiatives, migrating legacy ETL platforms like Informatica PowerCenter to modern cloud-native frameworks on AWS and Databricks using Python and PySpark.

This role is on-site.

Responsibilities

• Define solution architecture and modernization strategy for data pipelines, ensuring seamless migration from legacy systems.
• Lead onsite client engagement and delivery, managing relationships with business stakeholders and offshore engineering teams.
• Design and implement batch and streaming data architectures using AWS Glue, Databricks, and Apache Airflow.
• Drive data lakehouse implementation, focusing on data modeling, SQL optimization, and metadata management.
• Oversee large-scale programs across multiple workstreams, ensuring adherence to data governance and quality standards.

Required Skills

• 10+ years of experience in data architecture and ETL modernization.
• Strong hands-on expertise with Python, PySpark, and SQL for data engineering.
• Proven experience migrating from Informatica PowerCenter to cloud-native solutions.
• Deep knowledge of AWS services including S3, Glue, and Redshift.
• Experience with Databricks and Data Lakehouse concepts.
• Proficiency with Apache Airflow for workflow orchestration.
• Strong understanding of data warehousing, data modeling, and pipeline architectures.
• Experience leading onsite/offshore delivery models in client-facing roles.

Preferred Skills

• Experience in Capital Markets or Financial Services domains.
• Familiarity with data quality frameworks and AI/ML-based data solutions.

Key Skills

Education

Any Graduate