Sr. Developer

Cognizant Technology Solutions; Bengaluru; Hybrid; INR 900,000 - 1,500,000; Full time

Job summary

Cognizant Technology Solutions in Bengaluru is seeking a Sr Developer to design, build, and maintain data pipelines in a hybrid work model. You will work on end-to-end data engineering solutions using Amazon S3, Python, and Snowflake SQL for a global enterprise to enable secure analytics for business stakeholders.

The role emphasizes performance tuning, data quality, secure coding, and collaboration with product owners, analysts, and platform teams to deliver reliable, scalable data assets and

Qualifications

• 7-9 years of experience designing end-to-end data pipelines.
• Strong knowledge of data warehousing, ETL principles, and analytics needs.
• Excellent communication and cross-functional collaboration.

Responsibilities

• Design scalable data ingestion pipelines using S3 for enterprise analytics.
• Develop Python apps to automate data workflows.
• Build Snowflake data models (views/tables/procs) for performance.
• Collaborate with product owners to translate requirements into designs.
• Perform performance tuning for Python, Snowflake, and S3 access patterns.
• Implement data quality checks and validation frameworks.
• Apply secure coding and data protection practices across stacks.
• Troubleshoot production issues and implement durable fixes.
• Document architectures and data flows for maintainability.
• Coordinate with infra/platform teams to optimize resources in a hybrid setup.
• Mentor junior developers on S3, Python, Snowflake.
• Evaluate new features to improve reliability and value.
• Provide estimates and data-driven insights to stakeholders.

Skills

Data engineering

Python programming

Communication

Education

7-9 years in data pipelines

Tools

Amazon S3

Snowflake SQL

Python

Job description

Sr Developer role in a hybrid work model focusing on end to end data engineering solutions using Amazon S3 Python and Snowflake SQL for a global enterprise. The role designs optimizes and maintains robust data pipelines and platforms that enable secure scalable and reliable analytics capabilities for business stakeholders while ensuring best practices and continuous improvement in a day shift environment.

Responsibilities

• Design and implement scalable data ingestion pipelines using Amazon S3 to reliably collect organize and store large volumes of structured and semi structured data for enterprise analytics needs.
• Develop robust Python applications and scripts that automate data processing workflows improve system efficiency and reduce manual effort for business and technology teams.
• Build optimize and maintain Snowflake SQL data models including views tables and stored procedures to support high performance reporting and advanced analytical use cases.
• Collaborate with product owners business analysts and data consumers to translate complex functional requirements into clear technical designs and implementation plans that align with organizational objectives.
• Perform detailed performance tuning for Python code Snowflake SQL queries and Amazon S3 data access patterns to consistently achieve low latency and high throughput across critical workloads.
• Implement and maintain rigorous data quality checks reconciliation routines and validation frameworks to ensure that all data assets stored in Amazon S3 and Snowflake remain accurate complete and trustworthy.
• Apply secure coding and data protection practices in Python Snowflake SQL and Amazon S3 configurations to safeguard sensitive information and support compliance with internal policies and external regulations.
• Troubleshoot complex production issues across data pipelines storage layers and processing jobs using systematic root cause analysis and implement durable fixes that prevent recurrence and downtime.
• Document solution architectures data flows coding standards and operational procedures in a clear structured manner so that teams can easily maintain extend and reuse the implemented assets.
• Coordinate with infrastructure and platform teams to optimize resource usage schedule jobs appropriately and ensure that hybrid work arrangements support smooth collaboration and timely delivery of enhancements.
• Mentor junior developers in best practices for Amazon S3 Python and Snowflake SQL guiding code reviews encouraging clean design patterns and promoting continuous technical growth within the team.
• Contribute to continuous improvement by evaluating emerging features in Amazon S3 Python libraries and Snowflake capabilities and proposing pragmatic enhancements that increase reliability and business value.
• Support business stakeholders by providing accurate effort estimates transparent progress updates and data driven insights that help them make informed decisions and achieve measurable outcomes.

Qualifications

• Demonstrate advanced proficiency in Amazon S3 including bucket configuration lifecycle management data organization and secure access integration with data processing tools.
• Show strong hands on experience in Python programming for data engineering including writing modular code handling errors effectively and using relevant libraries for data manipulation and automation.
• Exhibit deep practical knowledge of Snowflake SQL including query optimization schema design time travel features and role based access to deliver performant and secure data solutions.
• Bring proven experience of seven to nine years in designing building and maintaining end to end data pipelines for enterprise scale environments preferably in a hybrid work setup.
• Possess solid understanding of data warehousing concepts ETL principles and analytics reporting needs so that implemented solutions directly support business decision making.
• Apply effective communication and collaboration skills to work smoothly with cross functional partners in a day shift ensuring timely alignment and clear expectation management.

Certifications Required good to have

• Demonstrate advanced proficiency in Amazon S3 including bucket configuration lifecycle management data organization and secure access integration with data processing tools.
• Strong hands-on experience in Python programming for data engineering including writing modular code handling errors effectively and using relevant libraries for data manipulation and automation.
• Deep practical knowledge of Snowflake SQL including query optimization schema design time travel features and role based access to deliver performant and secure data solutions.
• Seven to nine years of experience in designing building and maintaining end-to-end data pipelines for enterprise scale environments (hybrid work preferred).