Job Description

Role Purpose

Wipro Technologies invites applications for the position of Snowflake Data Engineer, where you will play a pivotal role in shaping robust, scalable cloud data infrastructure. As a key technical leader within the Applied AI & Data service line, you will collaborate cross-functionally with analytics, engineering, architecture, governance, and business teams to architect and maintain data ecosystems that promote data reliability, security, and governance. Your expertise will drive the transformation of disparate data sources into highly optimized, accessible data products tailored for advanced analytics and business intelligence.

We value innovation, efficiency, and a collaborative approach to solve complex data challenges. This role offers an exciting opportunity to contribute significantly to enterprise-scale data solutions while working within an energized team focused on digital transformation and sustainable data excellence.

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Key Responsibilities & Qualifications

• Design, develop, and optimize end-to-end data pipelines and ELT processes using Snowflake's platform capabilities to enable seamless ingestion, transformation, and consumption of data.
• Build and maintain robust data models including dimensional, normalized, and Data Vault models that support diverse analytical needs, ensuring flexibility and scalability.
• Leverage SQL, Python, and orchestration tools such as dbt, Airflow, or equivalent to create efficient data workflows, while implementing comprehensive automated testing and monitoring frameworks.
• Configure Snowflake virtual warehouses, clustering keys, resource monitors, and query profiles to maximize performance and cost-effectiveness.
• Implement and maintain strict data security measures including Role-Based Access Control (RBAC), masking policies, secure views, and data-sharing protocols to safeguard sensitive information in compliance with governance standards.
• Troubleshoot complex pipeline issues, data quality inconsistencies, and performance bottlenecks through detailed root-cause analyses and proactive resolution strategies.
• Collaborate with multi-disciplinary teams and stakeholders to translate complex business requirements into practical, scalable data solutions while adhering to Agile methodologies and participating in code reviews and continuous improvement cycles.
• Document technical designs, data lineage, operational procedures, and architecture decisions to support knowledge sharing and ongoing platform governance.
• Monitor usage metrics and provide actionable recommendations to enhance platform reliability, scalability, and cost optimization in dynamic cloud environments.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related technical discipline, or equivalent hands-on experience.
• Minimum of 5 years’ direct experience in data engineering roles with demonstrated capabilities in cloud-based data platforms, especially Snowflake.
• Proven expertise with Snowflake features including data ingestion with Snowpipe, Streams & Tasks for continuous data operations, Time Travel, zero-copy cloning, and semi-structured data handling (such as JSON, Avro, Parquet).
• Proficiency in SQL and Python scripting for complex data manipulation, automation, and workflow orchestration.
• Experience deploying ELT pipelines using modern orchestration tools like dbt, Apache Airflow, or Azure Data Factory.
• Familiarity with DevOps practices including version control with Git, CI/CD pipelines, automated testing, and deployment automation.
• Strong understanding of data modeling techniques, metadata management, data quality and governance frameworks.
• Exceptional problem-solving skills combined with the ability to manage diverse stakeholder relationships effectively.

Preferred Qualifications

• Certifications such as SnowPro Core & Advanced or relevant cloud/platform certifications (AWS, Azure, GCP).
• Experience with additional data technologies and platforms including Kafka, Fivetran, Power BI, Tableau, or Snowpark development.
• Knowledge of emerging architectural paradigms like data mesh, lakehouse, and experience with infrastructure as code and DevOps methodologies.
• Prior exposure to managing enterprise-grade, globally distributed data operations with regulated data requirements.

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Solution Design

As a Snowflake Data Engineer at Wipro Technologies, you will spearhead the design of scalable cloud data solutions tailored to client-specific business scenarios. You will facilitate technical design workshops and collaborate closely with project managers and technical architects to ensure solution alignment with enterprise architecture roadmaps and business objectives. Your role includes analyzing complex data integration challenges and architecting modular, reusable components that balance performance and maintainability.

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Coding, Configuration & Implementation

You will ensure high-quality code delivery by reviewing implementations thoroughly, resolving technical challenges within the engineering team, and establishing consistent data replication and transformation patterns compliant with project standards. Throughout the software development lifecycle, you will work with project managers and agile teams to ensure seamless integration, staging, and deployment of data solutions. Your role extends to implementing automated pipelines, validating configurations, and driving adoption through comprehensive user documentation and training materials designed to minimize operational risks and facilitate smooth transitions during deployments.

Additionally, you will proactively conduct root-cause analysis for recurring issues, optimize system performance, and recommend refinements to accelerate response times and enhance data reliability.

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Competencies and Skills

• Technical Expertise: Advanced proficiency in Snowflake data engineering, including architecture, ELT design, query optimization, and cloud integration.
• Communication: Clear, effective communication skills to engage diverse stakeholders, articulate complex technical concepts, and collaborate across multidisciplinary teams.
• Collaborative Working: Ability to foster a cooperative environment, working inclusively with peers, product owners, and business units.
• Passion for Results: Drive to deliver high-impact, quality solutions within defined timelines and budget, balancing innovation with practicality.
• Client Centricity: Focus on understanding client needs and delivering tailored solutions that drive business value.
• Learning Agility: Adaptability and eagerness to embrace emerging technologies, best practices, and evolving industry standards.
• Problem Solving & Decision Making: Analytical mindset to identify root causes of issues promptly and make informed, effective decisions.
• Execution Excellence: Commitment to rigorous implementation, testing, and continuous improvement to uphold operational excellence.