Description

You will design and maintain cloud data infrastructure, migrating on-prem data lakes to AWS or Azure while ensuring scalability and performance.

Responsibilities

• Architect and implement modern data lake solutions using AWS and Azure services including CloudFormation, IAM, Aurora, EventBridge, Lambda, and CloudWatch.
• Develop and optimize data models, stored procedures, and functions within relational databases such as Oracle, SQL Server, Postgres, or MySQL.
• Build and maintain real-time data streaming pipelines and analytics systems using Snowflake, SnowSQL, and SnowPark.
• Write efficient data processing code in Python, Spark, and SQL, leveraging big data tools like Hadoop, Hive, and NoSQL databases.
• Collaborate with stakeholders to define data governance standards and drive technical solutions in an agile environment.

Required Skills

• 8+ years of experience in data engineering, including supporting on-prem data lakes.
• 4+ years of hands-on experience with cloud platforms (AWS, Azure) and infrastructure-as-code (CloudFormation).
• 2+ years of experience with Snowflake (SnowSQL, SnowPark).
• 5+ years of experience with relational databases (SQL, stored procedures, functions) such as Oracle, SQL Server, Postgres, or MySQL.
• 5+ years of programming experience in Python, Spark, and SQL.
• Strong knowledge of data lake architecture, data modeling, and big data formats (Parquet, Delta, Iceberg).
• Solid experience with Linux OS and Shell Scripting.
• Bachelors’ degree in a relevant field.

Preferred Skills

• Experience in institutional asset management.
• Knowledge of Microsoft tools (Power BI, Synapse, Azure Data Factory).
• Experience with data governance technology tools.

Key Skills

Education

Any Graduate