Company: A Large Global Organization
Key Skills: Collibra, People Management, Python, ETL, Data Governance, Databricks
Roles and Responsibilities:
Design, build, and maintain data quality rules, checks, and controls across critical ETL/ELT pipelines and analytics domains. Lead implementation and expansion of data observability capabilities, including monitoring, alerting, and issue triage. Partner with engineering and platform teams to embed data quality and observability into pipelines, ingestion frameworks, and CI/CD processes. Perform root cause analysis for data quality incidents and coordinate remediation with upstream and downstream teams. Manage and mentor four Hyderabad-based data quality team members, including sprint planning, work allocation, performance coaching, and delivery accountability. Skills Required:
11 - 14 years of experience in data management, data analysis, data profiling,



and statistical techniques, including 5 years managing data engineering teams. ETL and data pipeline quality controls across ingestion and analytics ecosystems. Data governance expertise, including Collibra governance workflows and glossary/hierarchy concepts. Hands-on data quality and observability delivery, including monitoring/alerting and incident triage. Python, Py Spark, and advanced SQL for automation, data processing, and querying across multiple databases. Valuable to Have:
Databricks experience for building and operationalizing data quality checks in modern data platforms. Education: Relevant degree (or equivalent experience) in Computer Science, Engineering, Statistics, or a related field.

📌 Data management strategy (Hyderabad)
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📍 Hyderabad