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Group Head - Data Engineering

Group Head - Data Engineering

Hudson ManpowerMumbai
30+ days ago
Job description

Key Responsibilities :

  • Lead technical implementation of data pipeline and migration requirements, maximizing platform capabilities to support business stakeholder objectives.
  • Interface directly with stakeholders to gather requirements and deliver automated, end-to-end data engineering solutions.
  • Design and implement robust data pipelines to automate ingestion, transformation, and augmentation of structured, unstructured, and real-time data.
  • Drive continuous improvement by identifying, designing, and implementing process automation, optimizing data delivery, and re-architecting infrastructure for scalability.
  • Troubleshoot and resolve data quality issues flagged by pipeline monitoring or downstream consumers.
  • Enforce Data Governance best practices, including functional and technical impact analysis.
  • Provide technical guidance and innovative ideas to improve data systems and solutions.
  • Create and maintain clear documentation on data models, schemas, and transformation / validation rules.
  • Implement tools to enable faster data extraction, analysis, and visualization for data consumers.
  • Lead full software development lifecycle for batch ETL processes, including hands-on development, code reviews, testing, deployment, and documentation.
  • Collaborate closely with internal product and technical teams to ensure seamless integration of data infrastructure.
  • Migrate existing data applications and pipelines to cloud platforms (AWS), leveraging Platform-as-a-Service (PaaS) solutions.

Required Skills and Qualifications :

  • 7 to 12+ years of hands-on experience in SQL database design, data architecture, ETL development, data warehousing, data mart, data lake, Big Data, and AWS Cloud.
  • Strong knowledge of Data Governance principles and best practices.
  • Proven ability to design, build, and maintain scalable, automated data pipelines handling diverse data types and volumes.
  • Expertise in troubleshooting and resolving complex data quality issues.
  • Experience with cloud migration and cloud-native data solutions, particularly AWS PaaS offerings.
  • Strong problem-solving skills and ability to work closely with stakeholders to understand and translate business needs into
  • technical solutions.

  • Excellent documentation and communication skills.
  • Familiarity with software development lifecycle, code reviews, testing, and deployment in an Agile environment.
  • Bachelors or Masters degree in Computer Science, Information Technology, Engineering, or related fields.
  • Experience with modern data engineering tools and frameworks such as Apache Spark, Kafka, Airflow, or similar.
  • (ref : hirist.tech)

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