Strategic Data Leader

12 hours ago

Salem, Tamil Nadu, India beBeeData Full time US$ 2,00,000 - US$ 2,50,000
Chief Data Architect

Job Summary:

We are seeking an accomplished Chief Data Architect to lead our data engineering and analytics strategy, architecting scalable cloud-native data platforms and driving adoption of cutting-edge data architectures.

Key Responsibilities:

  • 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 Spark, Kafka, Delta Lake, and Snowflake.
  • 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:

To be successful in this role, you will need:

  • 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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