Sr. Data Engineer / Sr. BI Developer

Job Summary

Lead the offshore engineering pod responsible for analyzing, refactoring, testing, deploying, and stabilizing TIBCO BusinessEvents applications during the 5.5 to 6.4 upgrade, while driving Data Automation & AI and Data Engineering – Data Analytics – Databricks (Technical) initiatives as a Sr. Data Engineer / Sr. BI Developer. Candidate must have relevant experience of 8 to 12 Years.

Key Responsibilities

• Lead the offshore engineering pod responsible for analyzing, refactoring, testing, deploying, and stabilizing BusinessEvents applications during the 5.5 to 6.4 upgrade.
• Plan and assign application work by complexity, criticality, wave, environment, and acceptance criteria.
• Review scanner findings and remediation for deprecated APIs, legacy syntax, changed classes, channel types, and custom Java extensions.
• Enforce engineering quality across DEV, QA, PTEST, PROD, CI/CD deployments, defect resolution, and technical documentation.
• Support production cutovers, parallel-run validation, discrepancy analysis, hypercare, sign-off, and controlled 5.5 retirement.
• Apply Data Engineering – Data Analytics – Databricks (Technical) expertise to design, build, and optimize data pipelines and analytical solutions.
• Contribute to Data Automation & AI initiatives by implementing robust data ingestion, transformation, and automation frameworks aligned with business requirements.
• Collaborate with onshore and offshore stakeholders to ensure alignment of BusinessEvents upgrade activities with broader data and analytics objectives.
• Provide technical leadership, guidance, and mentoring to the offshore engineering team to ensure consistent delivery quality and adherence to best practices.
• Ensure proper documentation of application changes, upgrade impacts, and data engineering workflows to support maintainability and knowledge transfer.

Other Capabilities

• Ability to lead offshore engineering teams with clear allocation of work and accountability across the upgrade lifecycle.
• Strong problem-solving skills in analyzing production discrepancies, performance issues, and integration challenges across environments.
• Capability to work across Data Automation & AI and Data Engineering – Data Analytics – Databricks (Technical) domains, aligning technical solutions with business outcomes.
• Effective communication skills to coordinate with cross-functional teams and stakeholders during cutovers, parallel runs, and hypercare phases.
• Attention to detail in reviewing scanner findings, remediation plans, and technical documentation to maintain high engineering standards.
• Adaptability to work in a dynamic upgrade program, managing multiple waves, environments, and acceptance criteria concurrently.