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Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and maintain scalable data integration pipelines primarily using SnapLogic and Snowflake.
Optimize Snowflake data warehouse for performance, data modeling, and query efficiency.
Develop automation and data processing solutions using Python; manage batch jobs via Control-M and troubleshoot production issues.
Minimum Requirements
10–12 years of data engineering experience with 8 to 12 years relevant to SnapLogic and Snowflake.
Strong hands-on expertise in SnapLogic, Snowflake, Python, and Control-M is mandatory.
Experience with ETL/ELT pipelines, data modeling, Snowflake performance tuning, and large-scale enterprise projects.
Bachelor's or Master's degree in Computer Science, IT, Engineering, or related field.
Ideal Candidate Profile
Experienced in architecting and delivering data engineering solutions within Agile/Scrum environments, particularly involving cloud data platforms.
Capable of mentoring junior staff and collaborating with cross-functional teams including architects and business analysts.
Proficient in troubleshooting complex data pipeline failures and ensuring data quality, security, and scalability.