ETL Tech Lead [Canal Insurance]

Client: Canal Insurance

Role: ETL Team Lead

Location: Greenville, SC

Type : Contract to Hire

Visa: required non sponsorship visa candidates

Rate: Competetive

1. Production Support, Operations & Reliability
   • The ETL Team Lead owns end-to-end operational support for Canal's existing data stack:
     • Monitor daily ETL loads across SQL jobs, DHIC (GW DataHub and InfoCenter) and legacy SSIS packages.
     • Work with AMS team where necessary to troubleshoot pipeline failures, performance issues, schema mismatches, permissions issues, and cloud resource failures.
     • Work with AMS team where necessary to perform root-cause analysis and to implement permanent fixes.
     • Ensure SLA adherence and on-time delivery of critical reporting datasets for scheduled ETL jobs .
     • Provide direction for both AMS and ETL Developers for Legacy & Current ETL maintenance.
     • Refactor or retire outdated or redundant ETL processes.
2. Maintain and improve existing pipelines that utilize the following technologies:
   • Microsoft SQL Server Database programming
   • T-SQL Scripting
   • SQL Server Integration Services
   • Microsoft Powershell
   • Guidewire DataHub and InfoCenter
   • Oracle Database programming
   • Oracle PL-SQL Scripting
   • SAP BODS (SAP BusinessObjects Data Services)
   • PostgreSQL Scripting
3. Operational Excellence
   • Work with AMS team to assist with the creation and/or enhancement of operational runbooks, SOPs, monitoring dashboards, and incident response workflows.
   • Partner with other IT operational segments, business SMEs, and AMS team to minimize downtime and to ensure that business SLAs are met.
   • Improve upon existing, as well as implement new proactive for daily processing.
4. Business Continuity
   • Work with AMS team to ensure development support coverage for critical data pipelines (rotation-based).
   • Support month-end and quarter-end financial reporting cycles.
   • Coordinate production releases and validate deployments.
   • The ETL Tech Lead will become the steady-state technical owner of the entire data operations layer during the Canal modernization journey.
5. Technical Leadership & Collaboration
   • Serve as technical lead guiding onshore/offshore developers.
   • Review code, enforce best practices, and mentor junior engineers.
6. Partner with Scrum Masters, Project Mangers, Enterprise Architecture, QA Automation, Change Management, and AMS support teams.
7. Data Ingestion, ETL/ELT Development & Optimization
   • Develop reusable ingestion patterns for Guidewire DataHub and InfoCenter, HubSpot, Telematics, and other facets of the business.
   • Work with Canal Architects to modernize existing ETL workloads using Delta Lake, Medallion Architecture, and Fabric Lakehouse.
   • Build scalable data ingestion pipelines using potential upcoming technology (Azure Data Factory, MS Fabric , Databricks, Synapse Pipelines, etc.).
   • Work to bring in Internal and External integrations data into the platform.
8. Real-Time, Streaming & Event-Driven Engineering
   • Proven experience designing and implementing real-time data pipelines using Event Hub, Fabric Real-Time Analytics, Databricks Structured Streaming, and KQL-based event processing.
   • Develop and enable real-time operational insights and automation capabilities-including Telematics alerting, FNOL automation, and fraud/VNOS/VNOP detection-through event-driven architectures and streaming analytics.
9. Modern Azure Data Stack Leadership
   • Lead the strategy, design, and engineering of Canal's modern Azure data ecosystem using next-generation tools and Medallion Architecture, including:
     • Implementing Medallion Architecture (Bronze/Silver/Gold) across Fabric Lakehouse, Warehouse, Eventhouse, and KQL Database.
     • Leveraging Delta tables with schema enforcement, ACID compliance, and versioning.
10. Data Modeling, Curation & Governance
    • Develop curated, analytics-ready datasets to support Power BI, operational reporting, and advanced analytics use cases.
    • Assist Canal architect with implementation of Data Governance tools.
    • Establish robust data quality, validation, alerting, and observability frameworks to maintain accuracy, consistency, and trust in enterprise data.
11. AI/ML Data Enablement (Optional)
    • Prepare ML-ready datasets for pricing, risk, fraud detection, underwriting, claims leakage, and predictive insights.