About the role
from listingCompany Overview
DigitalXnode helps clients across industries connect with skilled and relevant talent for their technology and business requirements. We support hiring and staff augmentation needs by identifying professionals with the right expertise for different projects and engagement models. Our focus is on helping clients access suitable talent while creating meaningful professional opportunities across India.
Job Summary
We are looking for an experienced Senior Snowflake Data Engineer to work with our client in India. The role focuses on building and maintaining enterprise data pipelines, developing complex data transformations, implementing data-model changes, and improving data quality, performance, and cost efficiency. The ideal candidate should be comfortable working independently across BAU and change requests and supporting production data environments.
Key Responsibilities
Build, maintain, and optimise robust Snowflake data pipelines and complex data transformations.
Handle BAU (Business-As-Usual) activities and change requests to support ongoing engineering workloads.
Implement data-model updates and architectural changes defined by lead or principal data architects.
Design and build reusable data models, Dynamic Tables, Time Travel-based structures, and snapshot frameworks.
Develop automated reconciliation, data validation, and data-quality controls across data pipelines.
Monitor and improve Snowflake performance through query and warehouse tuning.
Support Snowflake cost optimisation and operational observability.
Follow Git-based development and CI/CD practices for database objects, code, and deployments.
Troubleshoot, debug, and independently resolve complex production data pipeline issues.
Work with engineering and architecture teams to deliver reliable and scalable data solutions.
Required Technical Skills
5–9 years of relevant experience in data engineering, preferably in enterprise environments.
Deep hands-on experience with Snowflake.
Strong expertise in Snowflake Dynamic Tables, Snowpark, Task History, and warehouse optimisation.
Advanced SQL skills, including complex joins, window functions, query optimisation, and performance tuning.
Proven experience building scalable ELT/ETL pipelines.
Strong understanding of dimensional data modelling, star schemas, and data warehousing principles.
Experience implementing data-quality frameworks, automated testing, validation, and reconciliation.
Proficiency with Git and CI/CD pipelines for code deployment and database version control.
Ability to troubleshoot and resolve complex data pipeline and production issues independently.
Preferred Technical Skills
Familiarity with MuleSoft or enterprise source integration patterns.
Experience with Snowpark-based development.
Experience designing reusable snapshot and historical-data frameworks.
Exposure to enterprise-scale data integration and operational monitoring.
Working knowledge of Python for data engineering or automation is an advantage.
Required Skills
Strong analytical and problem-solving ability.
Ability to work independently and take ownership of assigned workloads.
Attention to detail when working with data quality and reconciliation.
Ability to understand architectural designs and implement them accurately.
Strong troubleshooting and debugging skills.
Good communication and collaboration with architects, engineers, and business stakeholders.
AI Experience
AI experience is not specifically required for this role. Familiarity with AI-assisted development or data engineering productivity tools may be useful but is not mandatory.
Managerial Experience
Formal people-management experience is not mandatory. The role requires independent ownership of data engineering workloads and close collaboration with architects and engineering teams.
Operational Experience
Experience handling BAU and change requests in enterprise data environments.
Experience supporting production data pipelines and resolving operational issues.
Experience with CI/CD-based deployment and Git workflows.
Experience monitoring data quality, pipeline reliability, performance, and operational health.
Experience working with architecture-defined data models and enterprise integration patterns.
Qualifications
UG: Any Graduate. A degree in Computer Science, Information Technology, Engineering, Data Science, or a related field is preferred.
Certifications
Relevant Snowflake, cloud, data engineering, or database certifications are optional and may be an advantage.
Experience
5–9 years of relevant data engineering experience.
Submit Resume at apply@digitalxnode.com
Explore more job opportunities at Job Openings
Technology: Snowflake ELT ETL Snowpark Warehouse Optimization Snowflake Performance Tuning Data Pipelines Data Transformation Data Modelling
Job Type: Full Time / Part Time / Contractual
Job Location: Bangalore Chennai Delhi Gurgaon Navi Mumbai Noida Pune Nagpur Jaipur Ahmedabad Mumbai
Work Mode: Remote
Experience: 5 to 9 Years
Work Shift: India
Salary: Competitive
Sector: Data Engineering
Segment: Data Warehousing
Team Handled: No (Individual Contributor role)
Posting Date: 07/09/2026
Expiry Date: 07/10/2026
Employment type: Full-time
Industries: IT Services and IT Consulting