Deputy Manager Analytics

Role Brief -

As a Senior Snowflake Data Engineer, you will be responsible for designing, building, and scaling a modern cloud data platform that powers analytics, machine learning, and product intelligence across the organization. You will play a key role in building highly scalable data pipelines, optimizing the cloud data warehouse, and enabling reliable, secure, and high-performance data infrastructure.

This role requires deep expertise in cloud data engineering, strong problem-solving abilities, and the ability to collaborate closely with analytics, product, and engineering teams to transform raw data into trusted, business-ready datasets.

You will work with modern technologies including Snowflake, cloud infrastructure, orchestration frameworks, and BI platforms Tableau to support data-driven decision-making at scale.

We Need from you

• 4-8 years of experience in Data Engineering or Data Platform development.
• Strong hands-on experience building and managing enterprise-scale data warehouses in Snowflake.
• Proven expertise in designing and implementing highly scalable ETL/ELT pipelines.
• Advanced proficiency in SQL for complex transformations and performance tuning.
• Experience with orchestration frameworks such as Apache Airflow or similar workflow management tools.
• Experience building data models for analytics using Star Schema and dimensional modelling.
• Hands-on experience working with cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud.
• Experience working with large-scale datasets and distributed data processing systems.
• Strong understanding of data governance, security, and access control frameworks.
• Experience supporting BI and analytics platforms such as Tableau or Power BI.
• Experience collaborating with cross-functional teams including product managers, analysts, and other platforms teams.
• Experience in industry like Media, Entertainment, Digital, Telecom is Preferred

Skills Required

Cloud Data Warehouse

• Snowflake architecture and optimization
  • Data warehouse performance tuning
  • Data storage and compute management

Data Engineering

• ETL/ELT pipeline development
  • Workflow orchestration using Airflow or similar tools
  • Data ingestion frameworks and automation

SQL & Data Modelling

• Advanced SQL
  • Dimensional modelling
  • Fact and dimension table design

Cloud Platforms

• Snowflake, AWS / Azure / Google Cloud services
  • Cloud storage and compute services

Data Visualization & BI

• Tableau

Programming

• Python for data processing and automation
  • Scripting for pipeline automation

What will you do?

• Design and implement scalable data pipelines and cloud data warehouse architecture.
• Build and maintain high-performance ELT workflows in Snowflake.
• Develop and maintain data models optimized for analytics and reporting.
• Collaborate with analytics and BI teams to enable reliable datasets for dashboards and reporting.
• Optimize Snowflake warehouses for performance, scalability, and cost efficiency.
• Implement data governance, security policies, and access controls.
• Monitor data pipelines and implement robust data quality and reliability checks.
• Support advanced analytics and machine learning initiatives by enabling clean and structured datasets.
• Ensure data freshness, accuracy, and reliability
• Maintain documentation for data architecture, pipelines, and transformation logic.