Chief Data Strategist

6 days ago

Nagpur, Maharashtra, India beBeeData Full time US$ 17,50,000 - US$ 25,00,000
Job Overview:

The role of a Data Architect is pivotal in shaping the enterprise's data strategy, driving innovation and operational efficiency.

This position demands a unique blend of technical expertise in modern data engineering, coupled with a deep understanding of data science principles to unlock business value through data-driven decision making.

  • Enterprise Data Strategy

The successful candidate will be responsible for designing and implementing a comprehensive data architecture that integrates disparate systems, fosters collaboration across teams, and drives business outcomes.

Key areas of focus include:

  • Data Platform Strategy & Innovation

- Developing a strategic data vision aligned with enterprise AI and digital transformation goals.

- Designing scalable, cloud-native data platforms using cutting-edge technologies like Spark, Kafka, Delta Lake, and Snowflake.

  • Practice Building & Talent Development

- Building and scaling a high-performing team of data engineers, data scientists, and ML engineers.

- Crafting internal training programs and career pathways to upskill talent in data engineering, ML modeling, and analytics.

  • Engineering & Delivery Enablement

- Leading the development of reusable data pipelines, feature stores, and model training workflows.

- Implementing CI/CD and MLOps practices for seamless data and ML lifecycle automation.

  • Advanced Analytics & Data Science Enablement

- Enabling rapid experimentation and deployment of predictive models, optimization algorithms, and statistical analyses.

- Fostering collaboration between data scientists and engineers to operationalize models at scale.

  • Governance, Quality & Responsible Data Use

- Establishing robust data governance, lineage, and quality frameworks to ensure trust and compliance.

- Serving as a key stakeholder in data governance councils and model risk committees to drive accountability and transparency.

Qualifications:

  • Required:

- Bachelor's or Master's degree in Computer Science, Data Engineering, Statistics, or a related field.

- 10+ years of experience in data engineering, analytics, or data science roles, with proven leadership in building and scaling data and ML engineering teams.

  • Preferred:

- Experience in building Data & AI Centers of Excellence or technical communities of practice.

- Familiarity with GenAI, feature engineering at scale, and real-time inference systems.

- Certifications in cloud data services and MLOps platforms.

As a seasoned professional, you will have a strong track record of delivering high-impact projects, driving innovation, and fostering a culture of continuous learning and improvement.

We offer a dynamic work environment that values diversity, equity, and inclusion, with opportunities for growth and professional development. If you are passionate about data-driven transformation and excited about the prospect of joining a forward-thinking organization, please apply.

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