Senior Data Engineer

About Us:

Straive Private Limited (Erstwhile LearningMate Solutions Pvt. Ltd) is a global leader in data analytics and AI operationalization, helping enterprises embed advanced AI and data capabilities into core business workflows to deliver measurable business outcomes and ROI. With a workforce of 20,000 professionals serving 350+clients across 30+ markets, Straive combines technical scale with deep domain expertise. A key differentiator is its network of over 6,000 subject matter experts who specialize in managing and enriching complex, unstructured data—enabling organizations to build AI systems grounded in accuracy, context, and business relevance. The company continues to earn recognition from leading industry analysts and was recently named a Leader in AIM's 2026 Generative AI and Data Engineering PeMa Quadrants. Backed by EQT — a purpose-driven global investment organization which was ranked among the world's leading private equity firms by PEI in 2025 — Straive is positioned as a high-value alternative to traditional IT services providers, combining domain-led intelligence with AI execution at scale.

Role Summary

We are seeking an experienced Senior Snowflake Data Engineer to own, build, and optimize enterprise data pipelines and transformations. This role requires an independent practitioner capable of taking on BAU/change workloads, executing data-model architectures defined by lead architects, and driving data quality, performance, and cost management across our Snowflake environment. (Shift Time: 5:30 pm to 3:30 am)

What You Will Own & Drive

• Build and maintain robust Snowflake data pipelines and complex data transformations.
• Absorb and execute BAU (Business-As-Usual) and change requests to free up core engineering capacity.
• Implement data-model updates and architectural changes defined by the Principal Data Architect.
• Design and build reusable data models, dynamic tables, time-travel structures, and snapshot frameworks.
• Establish automated reconciliation mechanisms, data validation, and data-quality controls across pipelines.
• Maintain Snowflake performance, cost optimization (query/warehouse tuning), and operational observability.
• Support CI/CD practices and Git-based deployment workflows for database objects and code.
• Troubleshoot, debug, and resolve complex production data pipeline issues independently.

Must-Have Experience & Technical Skills

• Deep, hands-on Snowflake engineering expertise (Dynamic Tables, Snowpark, Task history, Warehouse optimization).
• Advanced SQL mastery, including complex joins, window functions, and performance tuning.
• Proven experience building scalable ELT/ETL pipelines in enterprise environments.
• Strong understanding of dimensional data modeling, star schemas, and data warehousing principles.
• Demonstrated experience implementing data-quality frameworks and automated testing/reconciliation.
• Proficiency with Git and CI/CD pipelines for automated code deployment and database version control.
• Familiarity with MuleSoft or enterprise source integration patterns is strongly preferred.