Data Support Specialist
NexionPro Services · Bangalore district, India
FULL TIME
Job Description
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.