Staff Software Development Test Engineer

Ovii's Interpretation of the Role

The Staff Software Development Test Engineer will own data quality for Tekion's Enterprise Data Platform, building automated testing frameworks and validation pipelines. Collaboration with data engineering, product, analytics, and AI teams ensures reliable, accurate data products and AI-driven insights.

Role Snapshot

• Staff-level test engineer
• Data platform quality ownership
• Automated testing framework design
• AI analytics validation
• On-site in Bangalore

Must-Have Requirements

• Test automation
• Data quality validation
• Data reconciliation
• AI evaluation
• Root cause analysis
• Data monitoring
• SDET for Data engineering

Work Setup

• Location: Bangalore, India
• Work mode: ONSITE
• Employment type: Full-Time

Not Specified in JD

• Salary range
• Visa sponsorship
• Remote eligibility
• Education requirement
• Certifications
• Relocation
• Notice period
• Travel
• Security clearance
• Coding test

What You'll Likely Work On

• Develop and maintain automated test suites for data pipelines, transformations, APIs, and platform features
• Validate data correctness, completeness, freshness, and lineage across the enterprise data lake
• Build reconciliation frameworks to compare lake outputs with source systems, product UIs, and business reports
• Define data quality metrics, validation rules, and monitoring alerts to catch anomalies early
• Partner with engineering teams to test new ingestion, transformation, and data‑sharing capabilities
• Create evaluation datasets and test strategies for the AI‑powered Analytics Agent, measuring accuracy and detecting hallucinations
• Drive root‑cause analysis of production data issues and implement preventive improvements
• Champion quality‑engineering best practices across the Data Platform organization

Good Fit If You Have

• Enjoys building robust, scalable test automation for complex data systems
• Comfortable collaborating with cross‑functional engineering and product teams
• Interest in AI/ML evaluation and data‑driven quality metrics