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We are looking for a
Data Run Support Engineer with strong experience in
AWS Data Engineering, Snowflake, Python/PySpark, SQL, and Production Support. The role is focused on maintaining and supporting production data pipelines, resolving incidents, ensuring data quality, monitoring platforms, and improving operational reliability.
The ideal candidate should be proactive, have strong troubleshooting skills, communicate effectively with technical and business stakeholders, and be capable of owning production issues from identification through resolution and RCA.
Key Responsibilities
- Monitor and support production data pipelines, data products, integrations, and analytics platforms.
- Investigate and resolve data failures, processing delays, pipeline failures, and production incidents.
- Perform Root Cause Analysis (RCA) and implement permanent corrective actions.
- Handle production incidents, service requests, and operational tickets using ServiceNow or similar ITSM tools.
- Troubleshoot data quality issues including missing, duplicate, inaccurate, or inconsistent data.
- Perform data reconciliation between source systems and downstream applications.
- Develop Python and SQL automation scripts for monitoring, validation, file processing, and operational activities.
- Troubleshoot and optimize Snowflake queries, warehouses, and data pipelines.
- Support ETL/ELT processes, data integrations, APIs, and file-based data processing.
- Monitor AWS data platforms, storage, compute, logging, and system performance.
- Support production releases, deployments, environment promotions, cutovers, and rollback activities.
- Maintain runbooks, technical documentation, support procedures, and incident records.
- Identify recurring production issues and proactively implement automation and preventive controls.
- Collaborate with platform teams, developers, business users, and other stakeholders during critical incidents.
- Drive improvements in MTTR, platform stability, monitoring, alerting, and operational efficiency.
Mandatory Technical Skills
- AWS Data Engineering
- Snowflake
- Python
- PySpark
- Strong SQL
- Production / L2-L3 Support
- ETL/ELT and Data Pipeline Troubleshooting
- Incident Management & RCA
- Data Quality and Data Validation
- AWS Monitoring & Logging fundamentals
- Strong troubleshooting and problem-solving skills
Good-to-Have Skills
- dbt – Models, testing, dependencies, troubleshooting
- GitLab – Branch management, deployments, and release support
- ServiceNow
- Data Observability / Monitoring / Alerting tools
- Tableau / Power BI
- SAP ECC / SAP S/4HANA
- Knowledge of SAP Procurement, Manufacturing, or Quality processes
- Release and Change Management
Required Soft Skills
- Excellent verbal and written communication
- High urgency for production-impacting issues
- Strong ownership and accountability
- Ability to own an issue from identification to resolution
- Proactive approach to troubleshooting and problem prevention
- Strong attention to detail
- Ability to work effectively with technical and business stakeholders
Ideal Candidate
The ideal candidate will be an
AWS Data Engineer with strong Snowflake, Python/PySpark, and SQL skills, combined with hands-on
production support experience. Candidates with strong incident management, RCA, data troubleshooting, automation, and stakeholder communication skills will be preferred.
Skills: snowflake,aws,python,sql,pyspark
