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