Senior Data Engineer

Job Responsibilities: Create/manage ETL pipelines for the data lake and Snowflake; automate data analysis/aggregation work. Design, build, and manage scalable ETL pipelines for a data lake and Snowflake environment, ensuring efficient data ingestion, transformation, and loading. Automate data analysis and aggregation processes to support business insights and reporting. Collaborate with cross-functional teams to optimize data workflows and maintain data quality. Key Skills: Data lake, AWS, ETL, Snowflake, Control‑M, Apache Airflow, PySpark, Java Spark Hiring Manager Notes: Experience: 5–10 years Project: Large-scale Financial Data Exchange & Data Security platform handling transaction processing and data movement. Role: 60% Data Engineering, 40% Programming (Python/Java). Must-Have Skills: PySpark (Strong hands-on experience) Apache Spark AWS Glue ETL AWS EMR Snowflake Python Java Data Structures & Algorithms AWS/Cloud Infrastructure Preferred Domain: Banking, Financial Services, Payments, Transaction Processing. Interview Process: Zoom interview with Live Coding; onsite may be required. Ideal Candidate: Senior Big Data Engineer with strong PySpark, AWS Glue/EMR, Snowflake, and Python skills, capable of building scalable financial data processing solutions.