Chief Data Strategist
2 weeks ago
Are you a visionary leader in data engineering?
Lead a Team of Data ExpertsAs Practice Lead – Data Practitioner, you will spearhead the development of scalable and high-performance data platforms. Your goal will be to design and execute a modern data strategy that aligns with enterprise AI and digital transformation objectives.
Key Responsibilities:- Data Platform Strategy & Innovation
- Create and implement cutting-edge data platforms using cloud-native technologies like Apache Spark, Kafka, Delta Lake, and Snowflake.
- Develop strategies for driving adoption of data mesh, lakehouse, and real-time streaming architectures.
- Practice Building & Talent Development
- Build and scale a high-performing team of data engineers, scientists, and ML engineers.
- Design internal training programs and career pathways to upskill talent in data engineering, ML modeling, and analytics.
- Engineering & Delivery Enablement
- Lead the development of reusable data pipelines, feature stores, and model training workflows.
- Implement continuous integration and delivery (CI/CD) and MLOps practices for data and ML lifecycle automation.
- 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.
Requirements:
- 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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