Data Support Specialist

Role Overview We are looking for a proactive Data Support Engineer to join our data engineering team. The role involves supporting, monitoring, and troubleshooting data pipelines and ETL processes, ensuring data reliability and smooth operations across Snowflake-based data platforms. Key Responsibilities Monitor and support daily data pipeline operations, ensuring timely and accurate data delivery. Perform L1/L2 troubleshooting for ETL job failures, data discrepancies, and pipeline errors. Write and optimize SQL queries for data validation, reconciliation, and issue resolution. Support and maintain Snowflake data warehouse objects, queries, and performance issues. Assist in developing and maintaining ETL workflows using Python and PySpark. Perform root-cause analysis for recurring data issues and support permanent fixes. Collaborate with data engineers and business teams to resolve data quality and pipeline-related tickets. Document issues, resolutions, and standard operating procedures for recurring support scenarios. Support production releases, deployments, and post-deployment validation. Mandatory Skills Snowflake – Hands-on experience with querying, basic administration, and troubleshooting ETL – Understanding of ETL/ELT concepts and pipeline workflows SQL – Strong query writing, debugging, and optimization skills Python – Working knowledge for scripting and automation PySpark – Basic to intermediate hands-on experience Good to Have Experience with cloud platforms (Azure/AWS/GCP) Exposure to job scheduling/monitoring tools Ticketing tool experience (ServiceNow, JIRA, etc.) Basic understanding of data warehousing concepts Experience in a production support/L1-L2 support environment Ideal Candidate A candidate with 1–3 years of experience who is comfortable working in a support-driven environment, has hands-on exposure to Snowflake, SQL, Python, and PySpark, and can quickly troubleshoot and resolve data pipeline issues under time-sensitive conditions.