Zensar Technologies—Senior Data Engineer – Snowflake Developer

Job description

Description: Key Responsibilities - Design, develop, and optimize ETL/ELT pipelines using Snowflake, SQL, and PySpark to support analytics and reporting needs. - Write complex, high-performance SQL queries and stored procedures; tune queries and warehouse configurations for cost and performance efficiency. - Develop and maintain SnowSQL scripts for data loading, transformation, automation, and orchestration within the Snowflake environment. - Build and manage data ingestion pipelines using Python and PySpark for large-scale structured and unstructured data processing. - Implement data modeling, schema design, and data quality/validation frameworks within Snowflake. - Manage Snowflake objects such as warehouses, databases, schemas, roles, and access controls, following best practices for security and governance. - Troubleshoot and resolve performance bottlenecks, data pipeline failures, and data quality issues. - Collaborate with business analysts, data scientists, and other engineering teams to understand requirements and translate them into robust technical solutions. - Document technical designs, data flows, and standard operating procedures clearly for team and stakeholder use. - Actively use AI-assisted tools (e.g., Copilot, ChatGPT, Claude, or similar) to accelerate coding, debugging, documentation, and query optimization tasks. - Mentor junior engineers and contribute to establishing engineering best practices within the team. Required Skills - Strong proficiency in SQL, including complex joins, window functions, query optimization, and performance tuning. - Solid working knowledge of Python, particularly PySpark, for data processing and transformation at scale. - Strong Snowflake development experience, including SnowSQL, Snowpipe, Streams, Tasks, and Snowflake's role-based access control model. - Experience designing and implementing data warehouse/data lake architectures on Snowflake. - Excellent verbal and written communication skills, with the ability to explain technical concepts to non-technical stakeholders. - Demonstrated ability to effectively use AI/GenAI tools to improve productivity in coding, testing, and documentation. - Familiarity with version control (Git) and CI/CD practices for data pipelines. Good to Have - Experience with orchestration tools such as Airflow, dbt, or Azure Data Factory. - Exposure to cloud platforms (AWS, Azure, or GCP) alongside Snowflake. - Knowledge of data governance, security, and compliance frameworks. - Prior experience working in Agile/Scrum delivery environments. Education : Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field (or equivalent practical experience).