Senior Snowflake Data Engineer

Infosys; Bengaluru; On-site; INR 3,500,000 - 6,500,000; Full time

Job summary

Infosys in Bengaluru seeks an experienced data architect to lead end-to-end Snowflake-based data warehouse and lakehouse efforts, aligning with analytics needs. You will design scalable data models, develop Python data processing components, and optimize Snowflake performance to meet business SLAs.

Ideal candidates have 8–12 years in data engineering, with deep Snowflake, Python, and SQL expertise, plus strong stakeholder communication and leadership capabilities.

Qualifications

• 8–12 years of overall experience in data engineering and platform delivery.
• 8+ years hands-on Snowflake experience: modeling, tuning, production support.
• 8+ years Python development for data engineering (processing, automation, integration).
• Strong SQL skills and building reliable data pipelines for analytics.
• Proven ability to lead design reviews and guide engineering practices.

Responsibilities

• Lead end-to-end design and implementation of Snowflake-based data solutions.
• Architect and optimize data models for reporting and analytics use cases.
• Develop and maintain Python data processing components and orchestration logic.
• Build and optimize Snowflake objects: databases, schemas, tables, views, tasks, streams.
• Tune Snowflake performance and Python workloads to meet SLAs.
• Establish data engineering standards for code quality, testing, and release management.
• Implement secure data access patterns and governance practices.
• Collaborate with stakeholders to translate requirements into designs and plans.
• Mentor team members through reviews and pair programming; troubleshoot production issues.

Skills

Snowflake architecture

Python data engineering

Pandas

PySpark

Orchestration

CI/CD for data platforms

Data quality & observability

Stakeholder communication

Education

Bachelor's or Master's degree in Computer Science or Engineering

Tools

Snowflake

Job description

Snowflake, Python Technology->Data on Cloud-DataStore->Snowflake Technology->->Python

Preferred Qualifications:

• Experience leading architecture for enterprise-scale Snowflake implementations, including multi-environment setup and workload isolation strategies.
• Strong experience with Python data engineering ecosystems (e.g., Pandas, PySpark) and building reusable frameworks/utilities.
• Expertise in orchestration and scheduling patterns for data workflows, including dependency management and monitoring.
• Experience implementing data quality checks, automated testing strategies, and observability for pipelines and datasets.
• Familiarity with CI/CD practices for data platforms, including version control, automated deployments, and environment promotion.
• Strong stakeholder management skills with the ability to communicate trade-offs, influence decisions, and align teams on technical direction.

Key Responsibilities:

• Lead end-to-end design and implementation of Snowflake-based data warehouse/lakehouse solutions aligned to business and analytics needs.
• Architect and optimize data models (dimensional, normalized, and hybrid) to support reporting, BI, and advanced analytics use cases.
• Develop and maintain Python-based data processing components, utilities, and orchestration logic to enable scalable data workflows.
• Build and optimize Snowflake objects including databases, schemas, tables, views, stages, file formats, tasks, streams, and stored procedures where applicable.
• Drive performance tuning across Snowflake (warehouse sizing, clustering, caching, query optimization) and Python workloads to meet SLAs.
• Establish and enforce data engineering standards for code quality, testing, documentation, and release management.
• Implement secure data access patterns, role-based access control, and governance practices to ensure compliance and auditability.
• Collaborate with stakeholders to translate requirements into technical designs, delivery plans, and measurable outcomes.
• Mentor team members through design reviews, pair programming, and technical guidance; lead troubleshooting and root-cause analysis for production issues.
• Coordinate with cross-functional teams to manage dependencies, risks, and delivery timelines for multiple concurrent initiatives.

Minimum Qualifications:

• Bachelor’s or Master’s degree (BTECH, MTECH, MCA, MSC) in Computer Science, Engineering, or a related field.
• 8–12 years of overall experience with strong ownership in data engineering and platform delivery.
• 8+ years of hands‑on experience with Snowflake, including data modeling, performance optimization, and production support.
• 8+ years of strong Python development experience for data engineering use cases (data processing, automation, and integration).
• Proven ability to lead technical design discussions, perform code reviews, and guide engineering best practices.
• Strong SQL skills and experience building reliable, maintainable data pipelines and datasets for analytics consumption.