Visionary Data Leader

2 days ago

Erode, Tamil Nadu, India beBeeDataStrategist Full time ₹ 30,00,000 - ₹ 50,00,000
Lead Data Strategist

The ideal candidate will lead the development of scalable, high-performance data platforms and advanced analytics capabilities across the enterprise. This role combines deep technical expertise in modern data engineering with a strong foundation in data science to enable data-driven innovation, operational efficiency, and AI readiness.

Key Responsibilities:

  • Data Platform Strategy & Innovation

    • Define and execute a modern data engineering and analytics strategy aligned with enterprise AI and digital transformation goals.

    • Architect scalable, cloud-native data platforms using technologies like Apache Spark, Airflow, dbt, MLflow, TensorFlow/PyTorch, and cloud data platforms (AWS/GCP/Azure).

    • Drive adoption of data mesh, lakehouse, and real-time streaming architectures.

  • Practice Building & Talent Development

    • Build and scale a high-performing team of data engineers, data scientists, and ML engineers.

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

    • Establish a 'ready-to-deploy' talent pool to support cross-functional data and AI initiatives.

  • Engineering & Delivery Enablement

    • Lead the development of reusable data pipelines, feature stores, and model training workflows.

    • Implement CI/CD and MLOps practices for data and ML lifecycle automation.

    • Promote modular, reusable components for data ingestion, transformation, and model deployment.

  • Advanced Analytics & Data Science Enablement

    • Enable rapid experimentation and deployment of predictive models, optimization algorithms, and statistical analyses.

    • Foster collaboration between data scientists and engineers to operationalize models at scale.

    • Support use cases across customer intelligence, operations, finance, and product analytics.

  • Governance, Quality & Responsible Data Use

    • Establish enterprise-wide data governance, lineage, and quality frameworks.

    • Ensure compliance with data privacy regulations (e.g., GDPR, HIPAA) and ethical AI standards.

    • Serve as a key stakeholder in data governance councils and model risk committees.

Qualifications:

  • 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.

  • Proven leadership in building and scaling data and ML engineering teams.

  • Hands-on expertise with tools like Apache Spark, Airflow, dbt, MLflow, TensorFlow/PyTorch, and cloud data platforms (AWS/GCP/Azure).

  • Strong understanding of data modeling, distributed systems, and ML lifecycle management.

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