Data Operations Lead/ Data Architect
Role details
Job location
Tech stack
Job description
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Partner with customers to position data as a strategic business asset, enabling them to differentiate through modern data platforms, BI, and advanced analytics solutions.
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Engage with business stakeholders, IT leadership, and enterprise architects to design and implement scalable, cloud-native data architectures, with a strong focus on AWS-based solutions.
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Define and drive enterprise data strategies and technology roadmaps, including architecture design, data modeling, and stepwise execution of modern data platforms supporting diverse analytics use cases.
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Lead Data & Analytics maturity assessments and strategy workshops, ensuring alignment with business goals around performance, scalability, flexibility, and cost optimization.
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Provide thought leadership on modern data and analytics technologies, enabling innovation in BI, advanced analytics, and predictive modeling.
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Design, prototype, and deliver end-to-end cloud data solutions, enabling new digital capabilities, especially in the Property & Casualty (P&C) Insurance domain.
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Act as a trusted technology advisor, driving adoption of modern data solutions to help organizations become data-driven enterprises.
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Evaluate customer cloud readiness and AWS adoption maturity; design and deliver structured capability-building and enablement programs.
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Collaborate with cross-functional teams including Data Engineering, Data Governance, BI/Analytics, and Business teams in complex enterprise environments.
Requirements
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15+ years of IT experience, including 4+ years in architecting and delivering cloud-native data solutions.
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Minimum 4+ years of hands-on experience in the Commercial P&C Insurance domain (mandatory).
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Strong expertise in implementing end-to-end Modern Data Platforms on AWS, using advanced processing frameworks such as Databricks.
Technical Skills
Data Platforms & Cloud
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Deep understanding of cloud-native data architectures, data engineering pipelines, and data management frameworks.
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Hands-on experience with AWS services (e.g., S3, Redshift, Glue, Lambda, EMR, Athena).
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Expertise in data warehouse design, dimensional modelling, and columnar database architectures.
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Experience with Snowflake and other modern data warehousing platforms.
Database & Programming (Mandatory)
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Strong hands-on expertise in Oracle PL/SQL (must-have) including performance tuning, complex query optimization, and stored procedure development.
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Experience working with relational and distributed databases across enterprise environments.
ETL / ELT & Data Integration
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Strong knowledge of ETL/ELT concepts and tools, including:
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Oracle Data Integrator (ODI) - preferred
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Experience with modern ETL frameworks and pipelines
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Exposure to streaming and real-time data processing, including technologies like Kafka (Confluent).
BI & Reporting
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Hands-on experience with BI and reporting tools, with preference for:
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WebFOCUS (added advantage)
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Other BI tools such as Tableau / Power BI
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Ability to translate business requirements into actionable dashboards and analytics solutions.
Advanced & Emerging Capabilities (Good to have)
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Exposure to NoSQL databases (key-value stores, document databases) and understanding of performance trade-offs.
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Experience in building data products, Data Mesh architecture, and decentralized data ownership models.
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Knowledge of machine learning and analytics solutions, including deployment using AWS SageMaker (preferred).
Insurance Domain Skills (Mandatory)
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Strong understanding of P&C Insurance business processes, including:
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Policy Administration
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Underwriting
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Claims Management
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Billing & Payments
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Experience working with insurance data models, regulatory reporting, and actuarial/analytics use cases.
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Ability to align data solutions with insurance-specific KPIs, risk modeling, and compliance requirements.