Senior Snowflake Developer | Snowflake DW, Advanced SQL, Python

Tata Consultancy Services Limited; Khordha, Hyderabad, Bengaluru; On-site; INR 1,200,000 - 2,600,000; Full time

Job summary

Tata Consultancy Services Limited in India is seeking a skilled Snowflake Data Engineer to design, develop, and optimize Snowflake-based data warehouse solutions for analytics and business needs.

You will build and tune ETL/ELT pipelines, implement data governance, security controls, and performance tuning across Snowflake workloads, leveraging Python or Scala for automation and real-time data ingestion with AWS S3 and Kafka.

Qualifications

• 4 to 10 years of IT experience with at least 3+ years hands-on in Snowflake Data Warehouse
• Strong expertise in Advanced SQL, query optimization, stored procedures, views, tasks, streams, and window functions
• Solid understanding of Data Warehousing concepts, dimensional modeling, Star/Snowflake schemas, SCD implementation, and ETL/ELT frameworks
• Proven experience designing and implementing large-scale data pipelines and data integration on Snowflake
• Hands-on experience with Snowflake features such as Snow pipe, Time Travel, Zero-Copy Cloning, Dynamic Tables, Data Sharing, RBAC, and Data Masking
• Strong programming skills in Python (preferred) or Scala for automation, data processing, and orchestration
• Experience with semi-structured data such as JSON, XML, Parquet, and Avro
• Knowledge of Kafka and real-time data ingestion patterns
• Experience with AWS S3 and cloud-native data architectures
• Strong Data Governance, Data Quality, Security, and Compliance practices
• Experience in performance tuning, troubleshooting, and optimizing Snowflake workloads
• Exposure to Snowflake Cortex AI/ML capabilities will be a plus
• Excellent problem-solving, communication, and stakeholder management
• Ability to work in fast-paced, cross-functional, and client-facing environment

Responsibilities

• Design, develop, and maintain scalable Snowflake Data Warehouse solutions
• Build and optimize ETL/ELT pipelines for data ingestion and transformation
• Develop and tune complex SQL queries, stored procedures, tasks, streams, and views
• Implement and manage Snow pipe, stages, and continuous data ingestion
• Work with structured and semi-structured data (JSON, XML, Parquet, Avro)
• Design data models including Star Schema and Snowflake Schema
• Collaborate with architects, data engineers, analysts, and stakeholders
• Develop automation using Python or Scala for data processing and monitoring
• Integrate Snowflake with AWS S3, Kafka, and other data sources
• Monitor, troubleshoot, and optimize Snowflake workloads and performance
• Implement data governance, data quality, security, and RBAC policies
• Perform data validation, reconciliation, and completeness checks
• Support data migration initiatives and modernize legacy workloads
• Leverage Cortex AI/ML features where applicable
• Contribute to architecture discussions, code reviews, and best practice adoption
• Create technical documentation and deployment procedures

Skills

Snowflake DW

Advanced SQL

Python

Scala

Data Modeling

Data Governance

Problem Solving

Stakeholder Management

Communication

Analytical Thinking

Tools

Snowflake

SQL

Python

Scala

AWS S3

Kafka

Parquet/Avro

Job description

• Design, develop, and maintain scalable Snowflake Data Warehouse (DW) solutions to support business and analytics requirements.
• Build and optimize ETL/ELT pipelines for ingesting, transforming, and loading data from multiple source systems into Snowflake.
• Develop and tune complex SQL queries, stored procedures, tasks, streams, and views to ensure high performance and efficient data processing.
• Implement and manage Snow pipe, stages, and continuous data ingestion frameworks for real-time and batch data loading.
• Work with structured and semi-structured data (JSON, XML, Parquet, Avro) and develop scalable data transformation solutions.
• Design and implement data models including Star Schema, Snowflake Schema, Dimensions, and Fact Tables.
• Collaborate with architects, data engineers, analysts, and business stakeholders to understand requirements and deliver data solutions.
• Develop automation and scripting solutions using Python (or Scala) for data processing, orchestration, validation, and monitoring.
• Integrate Snowflake with cloud platforms and services such as AWS S3, Kafka, and other enterprise data sources.
• Monitor, troubleshoot, and optimize Snowflake workloads, warehouses, caching mechanisms, and overall platform performance.
• Implement data governance, data quality, security, RBAC, masking policies, and compliance controls across the Snowflake ecosystem.
• Perform data validation, reconciliation, and completeness checks to ensure accurate and reliable data delivery.
• Support data migration initiatives and resolve challenges associated with migrating legacy data warehouse workloads to Snowflake.
• Leverage advanced Snowflake capabilities such as Time Travel, Fail-safe, Data Sharing, Dynamic Tables, Cortex AI/ML, and Zero-Copy Cloning where applicable.
• Participate in architecture discussions, code reviews, and best practice adoption to ensure scalable and maintainable data solutions.
• Create technical documentation, operational runbooks, and deployment procedures while providing production support and issue resolution.

Preferred candidate profile

• 4 to 10 years of overall IT experience with at least 3+ years of hands-on experience in Snowflake Data Warehouse.
• Strong expertise in Advanced SQL, query optimization, stored procedures, views, tasks, streams, and window functions.
• Solid understanding of Data Warehousing concepts, dimensional modeling, Star/Snowflake schemas, SCD implementation, and ETL/ELT frameworks.
• Proven experience designing and implementing large-scale data pipelines and data integration solutions on Snowflake.
• Hands-on experience with Snowflake features such as Snow pipe, Time Travel, Zero-Copy Cloning, Dynamic Tables, Data Sharing, RBAC, and Data Masking.
• Strong programming skills in Python (preferred) or Scala for automation, data processing, and orchestration.
• Experience working with semi-structured data such as JSON, XML, Parquet, and Avro.
• Good knowledge of streaming technologies such as Kafka and real-time data ingestion patterns.
• Experience with cloud storage platforms such as AWS S3 and cloud-native data architectures.
• Strong understanding of Data Governance, Data Quality, Security, and Compliance practices.
• Experience in performance tuning, troubleshooting, and optimizing Snowflake workloads and warehouses.
• Exposure to AI/ML capabilities within Snowflake, including Snowflake Cortex, will be an added advantage.
• Excellent problem-solving, communication, and stakeholder management skills.
• Ability to work in a fast-paced, cross-functional, and client-facing environment.