We are hiring for-

Snowflake Developer

Experience: 6-8 Years

Location: Location: Bangalore, Gurugram

Work Mode: Hybrid

Notice Period: Immediate / Short Notice Preferred

— Senior Snowflake Developer / Data Engineer

Role Summary

We are seeking a Senior Snowflake Developer / Data Engineer with 6–8 years of experience to design, build, and automate data pipelines on Snowflake, with a strong emphasis on Python-driven orchestration and integrating AI/LLM components into automated workflows. This role goes beyond writing SQL — it requires the ability to engineer end-to-end automation flows that connect data platforms, AI/ML components, and orchestration tooling to solve data movement, transformation, and migration problems at scale.

Key Responsibilities

- Design and build automated data pipelines on Snowflake using Python, connecting ingestion, transformation, and validation stages into a cohesive, repeatable flow
- Integrate AI/LLM components (e.g., Snowflake Cortex, LLM APIs, or similar AI services) into data pipelines to automate tasks such as code conversion, data classification, anomaly detection, or validation
- Architect and implement medallion-style (Bronze/Silver/Gold) data layers, with automated transformation logic rather than manual, one-off scripting
- Build orchestration and monitoring around automated pipelines (retry logic, error handling, logging, alerting) so pipelines run reliably with minimal manual intervention
- Evaluate where automation can replace or accelerate manual data engineering effort, and build the tooling to do so
- Troubleshoot and resolve failures in automated pipelines, including cases where AI-generated output requires refinement or correction logic
- Continuously improve pipeline accuracy and efficiency by feeding observed failure patterns back into the automation logic itself,



not just fixing individual outputs
- Collaborate with data architects, analysts, and stakeholders to translate data movement/migration requirements into automated, scalable solutions
- Document pipeline design, automation logic, and validation approach for team and stakeholder visibility

Required Skills & Experience:

Experience level

- 6–8 years of overall data engineering experience, with significant hands-on Snowflake development

Snowflake platform
- Solid hands-on expertise: virtual warehouses, Snowpipe/Snowpipe Streaming, Streams & Tasks, Time Travel, RBAC and masking policies
- Experience with Snowflake Cortex (AI/LLM functions) or demonstrated ability to integrate external AI/LLM services with Snowflake
- Strong SQL performance tuning (query profiling, clustering, materialized views/dynamic tables)

Python & automation
- Strong Python skills, specifically for building automation/orchestration pipelines — not just scripting, but designing pipelines that chain multiple components together reliably
- Experience connecting AI/ML components (LLM APIs, ML models, or AI-powered services) into a broader automated workflow
- Familiarity with orchestration frameworks or patterns (e.g., Airflow, Dagster, custom orchestration, or Snowflake-native Tasks/Streams) for scheduling and sequencing pipeline stages
- Comfortable building error-handling, retry, and monitoring logic around automated processes

Data engineering fundamentals




- Strong SQL across at least one traditional RDBMS (SQL Server, Oracle, PostgreSQL, etc.) in addition to Snowflake
- Experience with ETL/ELT pipeline design, data validation, and reconciliation approaches
- Understanding of data platform migration patterns — moving data and logic from a legacy system to a up-to-date cloud data platform

Working style
- Comfortable operating as a builder of automation, not just a consumer of tools — genuinely enjoys engineering the pipeline itself
- Able to work independently on ambiguous problems and design a solution architecture, not just execute a predefined task list
- Strong communication skills to explain automation design choices and trade-offs to both technical and non-technical stakeholders

Preferred / Nice-to-Have
- Experience with AI-assisted or automated code conversion tooling (e.g., SnowConvert, BladeBridge, or similar)
- Experience building custom automation that combines multiple AI/LLM calls in sequence (agentic-style workflows)
- Background in a regulated or data-sensitive industry (financial services, healthcare, insurance)
- Contributions to internal tooling, accelerators, or reusable automation frameworks at a previous employer
- Exposure to modern BI/analytics tools for downstream reporting integration

Success Metrics for This Role
- Automated pipelines built are reliable, maintainable, and require minimal manual intervention over time
- Demonstrated reduction in manual effort through automation, measurable against a defined baseline
- AI/LLM integrations perform accurately and their failure modes are well understood and handled
- Pipeline design and automation logic are clearly documented and can be maintained by others

Interested candidates please share your resume at [email protected]

📌 Snowflake Developer (India)
🏢 Qusonic Technologies
📍 India