Inian Patrick Antony Doss

Enterprise analytics & controls leader with 17 years in various domian data pipelines, fraud defenses, and regulatory-grade data quality. Designs and operates control-native data ecosystems—reconciliation, validation, lineage, observability, and evidence baked into every release—while modernizing SAS estates to SQL/Python on AWS without disrupting BAU. Partners with CIO/CRO/CDAO/Compliance/Internal Audit to reduce loss, strengthen governance, and improve SLAs and cost-to-serve. Known for incident command discipline, operating model design, and measurable business outcomes. Driving modernization through SQL/Python/AWS adoption, Pattern standardization and AI-assisted automation for validation and reconciliation and lineage workflows.

• Directed enterprise analytics and regulatory controls across 38 critical pipelines spanning Fraud, Deposits, and Claims, embedding reconciliation, validation, lineage, and evidence packs into CI/CD release gates.
• Target-state modernization (SAS → SQL/Python on AWS S3/Glue/Athena) with standards for control points, CloudWatch observability, and incident runbooks adopted by 5 global squads.
• Instituted cross-functional OKRs/KRIs for data quality, platform stability, and audit readiness, improving governance maturity across 3 business units.
• Built an engineering playbook (coding standards, peer reviews, DQ gates) reducing defect-escape by 42% and improving cycle time by 28% across BAU and modernization releases.
• Decommissioned 112 legacy SAS jobs and migrated 7 domains to AWS, driving 31% lower computing spend and 22% improvement in SLA adherence through optimized orchestration and monitoring.
• Enabled faster regulator/audit responses through standardized evidence packs and lineage traceability.
• Scaled delivery across 6 squads / 4 locations by mentoring 14 senior engineers and aligning 3 vendor partners to common quality and control standards.

• Chaired cross-functional design/release governance forums with CRO, CDAO, CIO.
• Owned risk signoffs, evidence packs, and control alignment for regulated platforms.
• Defined engineering & DQ standards adopted across 5 global squads.
• Partnered with Compliance, Internal Audit, Risk Ops to close audit issues and strengthen governance maturity.

• SAS (Base, Macro, PROC SQL)
• SQL
• Python (Analysis/Automation)
• Teradata
• DB2
• Postgres
• SQL Server
• AWS (S3, Glue, Athena, CloudWatch)
• Autosys
• GitLab
• JIRA
• Data Quality & Controls
• Fraud Analytics
• Regulatory Reporting Pipelines