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Manager - Data Engineer

RPG Group
Vadodara, IND
Manager · 5+ years experience
Onsite
Discovered 1 weeks ago
Data LakeData QualityETL/ELTData Governance

Full Job Posting

Key Responsibilities

  • Metadata Ownership (Schema Steward) Own and continuously update the Metadata Dictionary for all R&D domains. Define and standardize unique identifiers such as Variant_ID, Compound_ID, DOE_ID, Test_ID, etc. Maintain naming conventions, versioning rules, and schema evolution practices. Validate sample metadata records to ensure adherence to standards. Ensure metadata consistency across all tools, systems, dashboards, and analytical use cases. Collaborate with IT Architect and functional SMEs to maintain a robust metadata governance framework. 2. Data Engineering Responsibilities Support R&D tools data extraction, cleansing, normalization, and ingestion processes. Design and assist with structured file-drop or automated ingestion pipelines for Data Lake loading. Perform feasibility validation for Phase-2 integration candidates, assessing data availability, structure, volume, and integration complexity. Conduct data discovery and profiling to understand source system nuances. Collaborate with the Architect to ensure data models comply with designed contracts and metadata rules. Implement pipeline monitoring, error handling, and data quality checks. Required Skills & Qualifications Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field. 5–8 years of experience in data engineering, metadata governance, or related roles. Strong expertise in ETL/ELT tools, file-based integrations, and data transformation logic. Prior experience R&D data or laboratory/engineering data sources is a strong plus. Understanding of metadata frameworks, data dictionaries, and data governance processes. Ability to work across cross-functional teams and ensure strict adherence to data standards.

Qualifications

  • 5+ years of experience in this profile Reporting To Head of R&D/ Senior Manager Digital & Analytics Role Summary This role will serve dual responsibilities: Schema Steward (Metadata Owner) to maintain authoritative metadata standards, IDs, naming conventions, and data definitions across the Data Lake. Data Engineer to build, validate, and maintain extraction and file-drop pipelines from systems such as TDMS and PDM, ensuring high-quality, structured, and consistent data ingestion. The role ensures metadata consistency , technical feasibility , and smooth execution of integration activities across all phases. Key Responsibilities 1. Metadata Ownership (Schema Steward) Own and continuously update the Metadata Dictionary for all R&D domains. Define and standardize unique identifiers such as Variant_ID, Compound_ID, DOE_ID, Test_ID, etc. Maintain naming conventions, versioning rules, and schema evolution practices. Validate sample metadata records to ensure adherence to standards. Ensure metadata consistency across all tools, systems, dashboards, and analytical use cases. Collaborate with IT Architect and functional SMEs to maintain a robust metadata governance framework. 2. Data Engineering Responsibilities Support R&D tools data extraction, cleansing, normalization, and ingestion processes. Design and assist with structured file-drop or automated ingestion pipelines for Data Lake loading. Perform feasibility validation for Phase-2 integration candidates, assessing data availability, structure, volume, and integration complexity. Conduct data discovery and profiling to understand source system nuances. Collaborate with the Architect to ensure data models comply with designed contracts and metadata rules. Implement pipeline monitoring, error handling, and data quality checks. Required Skills & Qualifications Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field. 5–8 years of experience in data engineering, metadata governance, or related roles. Strong expertise in ETL/ELT tools, file-based integrations, and data transformation logic. Prior experience R&D data or laboratory/engineering data sources is a strong plus. Understanding of metadata frameworks, data dictionaries, and data governance processes. Ability to work across cross-functional teams and ensure strict adherence to data standards.

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