Description

You will lead the design and implementation of scalable, efficient data architectures for real-time and batch processing.

This role is hybrid.

Responsibilities

• Design and implement complex data pipelines for real-time and batch processing.
• Drive, establish, and enforce data governance policies and quality frameworks.
• Analyze and optimize system performance for large-scale data operations.
• Mentor junior engineers and provide technical guidance on data best practices.
• Review and approve code promotions, enforcing release management procedures.

Required Skills

• 6+ years of experience in data engineering.
• Deep expertise designing metadata-driven, automated data pipeline solutions using cloud data technologies.
• Strong hands-on experience building ELT pipelines, Snowpipe, and DBT Cloud transformations in Snowflake.
• Proficiency in Python/PySpark and advanced SQL for ingestion and automation.
• Experience architecting solutions using AWS services like S3, Lambda, SQS, SNS, and Glue.
• Strong experience designing data integrity solutions across sources like SQL Server, Oracle, and Mainframe-DB2.
• Proficiency with orchestration tools including DBT Cloud and Astronomer Airflow.
• Experience implementing data security strategies like tokenization and dynamic data masking in Snowflake.
• Familiarity with data formats including JSON, XML, and CSV.

Preferred Skills

• Experience with Qlik for data visualization and reporting.
• Proficiency with GitLab and GitHub for version control and CI/CD.

Key Skills

Education

Any Graduate