Data Architect and Innovation Leader

1 week ago

Surat, Gujarat, India beBeeData Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Chief Data Innovation Officer

The Chief Data Innovation Officer will lead the development of cutting-edge data platforms and advanced analytics capabilities across the enterprise.

This role is responsible for defining and executing a modern data engineering and analytics strategy aligned with enterprise AI and digital transformation goals.

The ideal candidate will architect scalable, cloud-native data platforms using technologies like Spark, Kafka, Delta Lake, and Snowflake.

They will drive adoption of data mesh, lakehouse, and real-time streaming architectures.

Additionally, they will build and scale high-performing teams of data engineers, data scientists, and ML engineers.

Key responsibilities include designing internal training programs and career pathways to upskill talent in data engineering, ML modeling, and analytics.

They will establish a 'ready-to-deploy' talent pool to support cross-functional data and AI initiatives.

Furthermore, they will lead the development of reusable data pipelines, feature stores, and model training workflows.

They will implement CI/CD and MLOps practices for data and ML lifecycle automation.

Promoting modular, reusable components for data ingestion, transformation, and model deployment is also a key responsibility.

Moreover, they will enable rapid experimentation and deployment of predictive models, optimization algorithms, and statistical analyses.

They will foster collaboration between data scientists and engineers to operationalize models at scale.

Supporting use cases across customer intelligence, operations, finance, and product analytics is also a key aspect of this role.

Finally, they will establish enterprise-wide data governance, lineage, and quality frameworks.

Ensuring compliance with data privacy regulations (e.g., GDPR, HIPAA) and ethical AI standards is also a critical responsibility.

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.

• 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.

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.

• Recognized thought leadership in data engineering or data science (e.g., speaking engagements, publications, OSS contributions).

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