Senior Data Engineer Snowflake

Essential Skills

• Advanced Snowflake expertise (architecture, optimization, governance).
• Strong hands-on experience with Snowflake (data warehousing, performance tuning, security).
• Strong SQL skills with stored procedure development.
• Solid understanding of SQL and advanced query optimization techniques.
• Strong leadership in SQL-based ETL and stored procedure frameworks.
• Deep understanding of retail data domains and compliance frameworks.
• Proven experience in cloud-native ETL (Informatica, Talend).
• Experience in managing cross-functional teams and delivery pipelines

Desirable Skill

• Exposure to ML pipelines for retail analytics.
• Strategic experience in cost optimization and performance tuning.
• Strategic use of Cortex for innovation and advanced analytics.

Qualification:

• Experience: 7–10 years in data engineering, with 5+ years in Snowflake leadership/managerial roles.
• Education: Bachelor’s or master’s degree in computer science, Data Science, Bioinformatics, or related field.

Qualities:

• Strong analytical and problem-solving mindset.
• Detail-oriented with a focus on data accuracy and compliance.
• Excellent communication and stakeholder management skills.
• Ability to work independently and collaboratively in cross-functional teams.
• Adaptability to fast-paced and regulated environments.

Roles and Responsibilities

Job Title: Senior Data Engineer-Snowflake

Purpose of the Position: To lead the data engineering team in architecting and delivering enterprise-scale Snowflake solutions for retail analytics, ensuring alignment with strategic business goals and modernization initiatives.

Work Location: Chennai/Bangalore/Pune/Nagpur

Key Result Areas and Activities:

• Data Pipeline Development: Drive ingestion and transformation of multi-source retail data (MMS, CRM, Workday, Courion etc).

• Architecture Leadership: Define and implement Snowflake architecture for multi-layered retail data processing.

• ETL Strategy: Lead migration strategy from Netezza to Snowflake, ensuring automation and scalability.

• ETL Development: Build and optimize ETL workflows using Informatica, AWS Glue and SQL stored procedures.

• Strategic Alignment: Align data engineering practices with retail business priorities (sales, customer, workforce, inventory)

• Data Modelling: Create and maintain Snowflake tables and layered views for business consumption.

• Data Governance: Implement standards for lineage, documentation, and compliance.

• Collaboration: Coordinate with team members, work closely with data analysts, business stakeholders, and regulatory teams to understand data needs and deliver solutions.

• Performance Optimization: Ensure efficient query performance,  storage management and cost-effective data processing in Snowflake.

• Documentation & Governance: Maintain clear documentation of data models, transformations, and lineage to support audit and compliance requirements.

• Team Leadership: Mentor and manage engineers across different levels, ensuring delivery excellence.

• Innovation: Explore snowflake features like dynamic tables, automation, and advanced Snowflake features for efficiency.