Job description
Support Engineer - - - - - - - - - - -
- Key Responsibilities needed Data Platform Support & Operations Provide L2 support for data pipelines, ETL processes, and data platforms Monitor data workflows to ensure data availability, accuracy, and timeliness Manage and resolve production incidents, data failures, and performance issues Monitoring & Reliability (SRE Practices) Implement and manage monitoring, alerting, and logging frameworks Define and track SLIs/SLOs for data pipelines and platforms Ensure proactive issue detection and high system reliability Incident & Problem Management Perform root cause analysis (RCA) for data issues and system outages Work on incident resolution within defined SLAs Collaborate with engineering teams to implement permanent fixes and improvements Data Quality & Governance Ensure data integrity and consistency across systems Implement validation checks and automated quality frameworks Support compliance with data governance and security standards Collaboration & Stakeholder Management Act as a bridge between data engineering, BI, and business teams Communicate incident status, risks, and resolutions effectively Support stakeholders in resolving data-related issues and queries Continuous Improvement & Automation Identify opportunities to automate repetitive support tasks Improve system efficiency through process optimization Contribute to initiatives such as Data Driven Engineering (DDE) and automation frameworks Qualifications & Experience Bachelor’s/Master’s degree in computer science, Engineering, or related field Hands-on experience with: Data pipelines (ETL/ELT tools) SQL and data querying Cloud platforms (Azure preferred) Monitoring/logging tools Technical Skills Data Platforms: Fabricks, Azure Data Factory, Databricks, Synapse, or equivalent Databases: SQL Server, Snowflake, or similar Monitoring: Azure Monitor, Log Analytics, Grafana, Splunk (or equivalent) Scripting: Python, SQL, or Shell scripting BI Tools: Power BI DataIKU (Optional)