Title: Data Engineer(Snowflake)

Location: Primary: Hyderabad, India. Other locations: Mumbai/Pune

Employment Type: Remote,Hybrid

Snowflake certification is Must.

We are a specialized professional services and consulting firm focused on Data, AI, and Enterprise Architecture. We partner with enterprise clients to design and deliver modern data platforms, AI and GenAI solutions, knowledge graph architectures, cloud infrastructure, analytics, and enterprise transformation programs. Our work is hands-on, client-embedded, and outcome-driven - we architect and build, not just advise.

We serve clients across ten industries: Financial Services & Insurance, Healthcare & Life Sciences, Retail & Consumer Goods, Manufacturing & Supply Chain, Technology & Telecommunications, Energy & Utilities, Media & Entertainment, Government & Public Sector, Education & EdTech, and Hospitality & Travel.

Our five core capability areas that these roles directly support are: Contemporary Supply Chain & Operations, Enterprise Office Transformation, Growth & Revenue AI, Legal & HR Next, and Finance AI

Role Overview

- We are seeking a motivated Data Engineer with solid hands-on experience building and operating data pipelines, integrations, and models in production environments.
- This is a hands-on engineering role. You will build, test, and maintain the data pipelines, transformations, and data products that underpin our clients' data platforms, working from designs set by senior architects.
- You will help implement modern data platforms, integration flows, and AI-ready data foundations, and increasingly take ownership of well-scoped components of the architecture as you grow.
- Work closely with senior data architects, other data engineers, AI engineers, and delivery leads.




- Contribute to technical standards, reusable assets, and code quality within the engineering team.

Key Responsibilities

- Build and maintain ingestion, integration, transformation, and orchestration pipelines.
- Implement ETL/ELT, API, CDC, and streaming integration patterns under architectural guidance.
- Develop and maintain logical and physical data models.
- Build and support data products, including documentation of schemas and data contracts.
- Write clean, tested, well-documented, production-grade code.
- Implement metadata, lineage, data quality checks, and monitoring for pipelines you own.
- Support analytics, ML, and GenAI use cases by delivering reliable, well-structured data.
- Troubleshoot pipeline issues and participate in performance tuning and optimization.
- Follow and help refine engineering standards and reusable patterns set by the architecture team.
- Participate in code reviews and pair with peers; take direction from senior architects on design decisions.

Required Experience and Skills

- 36 years of experience in data engineering or a closely related role.
- Strong hands-on coding ability (Python and/or SQL) for building data pipelines.
- Practical experience with ETL/ELT tools and workflow orchestration (e.g., Airflow, dbt, or similar).
- Working knowledge of at least one major cloud data platform (Snowflake, AWS, Azure, or GCP).




- Understanding of data modeling fundamentals (dimensional modeling, normalization).
- Exposure to data warehouses or lakehouses in a production setting.
- Basic understanding of data governance concepts: metadata, lineage, and data quality.
- Good communication skills and ability to document work clearly.
- Comfortable working independently on well-defined tasks and asking for guidance on ambiguous ones.

AI and Modern Engineering Exposure (Good to Have)

- Familiarity with LLM/GenAI concepts and basic RAG pipelines.
- Exposure to vector databases or knowledge graphs.
- Experience using AI-assisted coding tools such as Claude Code, Cursor, or GitHub Copilot.
- Interest in prompt engineering and workflow automation.

Mindset

- Eagerness to learn and grow into more architectural responsibility over time.
- Ownership of assigned tasks and reliable follow-through.
- Comfortable in a fast-paced, startup-like environment.
- Open to feedback and continuous improvement.
- Collaborative team player who communicates proactively.

Education

- Bachelor's degree in Computer Science, Engineering, or a related field.
- Relevant cloud/data certifications are a plus.

Why Join Context66

- Work on contemporary data and AI platforms for enterprise clients.
- Learn directly from experienced data architects and AI engineers.
- Gain exposure to cutting-edge AI-native engineering practices.
- Clear growth path toward senior data engineering and architecture roles.
- Be part of building a fast-growing Data, AI, and Enterprise Architecture company.

We are looking for engineers who combine strong execution, curiosity, and a genuine interest in growing their architectural thinking over time.

📌 Snowflake Data Engineer (Hyderabad)
🏢 Kalpavruksh Systems
📍 Hyderabad