Lead Software Engineer - Cognos, BO, Snowflake,SQL

• Build and enhance end-to-end BI solutions: requirements → data modeling → report/dashboard development → testing → production support.

• Deliver the SAP BO exit outcomes by migrating and modernizing reporting content into IBM Cognos, including report rebuilds, validation, scheduling, and cutover support.

• Develop and maintain IBM Cognos reports, packages, and frameworks (Framework Manager / data modules as applicable).

• Design performant datasets and reporting layers on Snowflake and/or Databricks, including SQL optimization and cost/performance tuning.

• Partner with data owners and data engineering to align reporting to governed, reusable datasets and data products (MDL aligned), reducing point-to-point extracts and improving consistency.

• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.

• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation. Follow SDLC practices (version control, peer reviews, release management) and contribute to standards for BI development.

• Implement data quality checks, reconciliation, and monitoring to ensure trusted reporting during migrations and ongoing operations.

• Support incident triage and root-cause analysis for reporting/data issues drive permanent fixes and documentation.

• Contribute to long-term BI consolidation by building reusable metric definitions, semantic objects, and migration playbooks that support future dashboard and self-service tooling adoption (including Sigma where applicable).

• Participate in Sigma Computing PoC - build dashboards, connect to Snowflake/Databricks via MDL. Collaborate with data owners to register data sources to MDL. Assess and migrate Tableau/QlikSense dashboards to Sigma. Evaluate Sigma maturity for future Cognos workload migration. Support AI/conversational analytics enablement

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Strong hands-on experience with SAP Business Objects and IBM Cognos (report authoring, packages/models, scheduling, performance troubleshooting).
• Hands-on experience with Snowflake and/or Databricks (SQL, data modeling, working with large datasets).
• Strong SQL skills (joins, window functions, aggregations, query tuning).
• Experience delivering production-grade reporting/analytics solutions with attention to reliability, supportability, and governance.
• Ability to translate business requirements into scalable reporting and data designs, including migration and coexistence scenarios.
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations experience coaching engineers on safe, compliant adoption within delivery practices
• Hands-on experience with one of the tool QlikSense or Tableau or Sigma- dashboarding, data visualization best practices, migration experience
• BI (reports/dashboards) end to end migration project experience (any platform). Experience analyzing, rationalizing, and migrating large report inventories, including prioritization, wave planning, and execution tracking.
• Working knowledge of data warehousing concepts (for example: dimensional modeling, facts and dimensions, and data marts) sufficient to assess migration impacts and dependencies.

Preferred qualifications, capabilities, and skills

• Sigma (workbook/dashboard development, warehouse-native analytics concepts)
• Cloud data platforms - AWS, data lake architectures, MDL / data mesh / data product concepts
• Experience using analytics automation or artificial intelligence-enabled tools (e.g. Databricks Genie, Snowflake Cortex, Chat GPT/Copilot)to accelerate dataset analysis or workflow efficiency in a controlled enterprise environment.
• Python (data processing, automation, testing, utilities).
• Experience creating migration factory tooling, templates, or automated validation for large report portfolios.
• Financial services / Capital Markets / CIB domain experience