Description

You will design and implement enterprise-wide data architecture solutions for large-scale financial services environments.

This role is on-site.

Responsibilities

• Design conceptual, logical, and physical data models supporting operational, analytical, and reporting platforms.
• Architect cloud-native data platforms, including modern data lakes and warehouses.
• Develop scalable batch and real-time data integration solutions for structured and semi-structured data.
• Implement data quality, metadata management, lineage, and governance frameworks.
• Support Master Data Management (MDM) initiatives across security, account, client, and reference data domains.

Required Skills

• 8–10 years of experience in Enterprise Data Architecture and Data Modeling.
• Hands-on experience with Data Engineering and scalable data pipelines.
• Strong SQL expertise with programming in Python, PySpark, or Snowpark.
• Experience with dbt (Data Build Tool) for modular, reusable SQL-based workflows and ELT pipeline development.
• Proficiency with cloud platforms (Azure, AWS, or GCP) and integration with Snowflake or Databricks.
• Experience designing ETL/ELT frameworks using Spark-based pipelines or Snowflake tasks and streams.
• Knowledge of Master Data Management (MDM) and enterprise data governance frameworks.
• Familiarity with API integration, real-time/streaming data pipelines (e.g., Kafka, Spark Streaming).
• Understanding of security, compliance, and governance standards, including role-based access and encryption.

Preferred Skills

• Experience supporting enterprise modernization and cloud transformation initiatives.
• Financial Services or Investment/Wealth Management domain experience.

Key Skills

Education

Bachelor's degree