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Data Management & Data Delivery

Data Management & Data Delivery

Vrinda GlobalPune (division)
10 days ago
Job description

Qualifications :

  • Bachelor’s or Master’s degree in Data Science, Information Technology, Business Administration, or a related field.
  • Proven experience in winning and delivering accounts within the data management domain or similar industries.
  • 20+ years of experience in data-related project delivery, including 10+ years in a leadership or delivery management role.
  • Strong knowledge of data engineering, data warehousing, data lakes, cloud platforms (e.g., AWS, Azure, GCP), and data governance frameworks.
  • Experience with Agile, Scrum, and / or hybrid project management methodologies.
  • Excellent leadership, communication, and stakeholder engagement skills.
  • Proven ability to lead cross-functional teams in a matrixed organization structure.

Ability to oversee the technical aspects of data value chain

o Understand data ecosystem – data strategy aligning with business

goals, data governance, quality, medallion architecture, and so on

o Oversee the design and implementation of modern data platforms

o Manage proposals and projects involving cloud service providers

(e.g., AWS, Azure, Google Cloud)

o Ensure the efficient and secure integration of cloud services with

existing data systems

o Optimize cloud-based data storage and processing solutions for

performance and cost-effectiveness

  • Experience with the key elements of data lifecycle while designing and
  • recommending data solutions to clients :

    o Scalable Data Architectures

    o Integration of various data sources, ensuring that data is collected,

    processed, and made available in a structured manner.

    o Data Security and Compliance : Ensure that data systems comply

    with relevant security and privacy regulations, including GDPR,

    HIPAA, etc., and are secure from threats.

    o Data Pipeline Management : Design, development, and

    optimization of data pipelines to ensure high-quality, efficient data

    flow & storage.

    o Performance Optimization : Continuously monitor and optimize

    data workflows, addressing bottlenecks and improving speed.

    o Ensure Data Quality : Robust data validation and quality checks to

    ensure the accuracy, consistency, and completeness of the data

    o Data Governance : Establish data governance frameworks,

    policies, and processes to ensure proper data stewardship,

    security, privacy, and compliance (e.g., GDPR, HIPAA).

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