Chief Data Strategist

4 days ago

Delhi, Delhi, India beBeeData Full time ₹ 15,00,000 - ₹ 20,00,000

Maximize your impact as a visionary Data Architect responsible for crafting cutting-edge data solutions and spearheading innovative initiatives. This pivotal role demands expertise in designing, implementing, and maintaining robust data architectures that drive business success.

Key Responsibilities
  • Data Architecture Design: Develop scalable data pipelines and infrastructure to efficiently process, store, and analyze large volumes of data, aligning with business requirements.
  • Integrated Data Systems: Seamlessly integrate data from various sources (databases, APIs, streaming platforms) while ensuring reliable collection and maintaining data integrity.
  • Advanced Data Modeling: Design and implement complex data models to optimize storage and retrieval, based on project needs.
  • Efficient ETL Process Development: Craft ETL processes to extract, transform, and load data into target systems, leveraging scripts or ETL tools for automation.
  • Comprehensive Data Governance: Establish data quality checks and governance policies, including tracking data lineage, stewardship, metadata management, and building business glossaries.
  • Optimized Data Lakes and Warehousing: Design and maintain large-scale data lakes and warehouses for structured, semi-structured, and unstructured data, integrating with big data processing frameworks and machine learning tools.
  • Enhanced Data Security: Implement robust security measures, technologies, and policies to protect data throughout its lifecycle, ensuring compliance with regulations like DPDP and GDPR.
  • Database Optimization: Administer and optimize relational and NoSQL databases to effectively manage large data volumes.
  • Smooth Data Migration: Plan and execute data migration projects, ensuring minimal downtime and data consistency.
  • Scalable Data Pipelines: Optimize data pipelines for performance and scalability, identifying bottlenecks and implementing caching and indexing strategies.
  • Collaborative Environment: Collaborate with data scientists, analysts, and stakeholders to understand data requirements and provide access to necessary resources.
  • Documentation Excellence: Document data models, pipelines/ETL processes, and system configurations, providing training for sustainability and maintainability.
  • Staying Ahead: Engage with the community and participate in relevant programs to enhance skills and stay updated with the latest technologies and trends.
Qualifications and Skills
  • A Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or an equivalent field.
  • Strong understanding of database management systems (e.g., MySQL, PostgreSQL), NoSQL databases (e.g., MongoDB, Cassandra), and data modeling techniques.
  • Experience with big data technologies (Apache Hadoop, Spark), ETL tools (Apache NiFi, Talend), and data warehousing solutions (Amazon Redshift, Google BigQuery).
  • Knowledge of data governance principles, best practices for ensuring data quality and security, and compliance with DPDP, GDPR, HIPAA, or PCI DSS.
  • Cloud computing experience with AWS, Azure, or Google Cloud and their respective data services.
  • Real-time data processing framework familiarity (Apache Kafka, Apache Flink).
  • Analytical thinking and problem-solving abilities for resolving bottlenecks and optimizing systems.
  • Effective communication and collaboration skills.

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