Title: Data Engineer

Location: Primary: Hyderabad, India. Other locations: Rest of India

Employment Type: Full-time, Remote

We help enterprises transform fragmented data, systems, documents, and business knowledge into trusted, governed, reusable, and AI-ready enterprise context. Our work spans modern data foundations, enterprise data architecture, integration, semantic layers, knowledge graphs, GraphRAG, ontologies, metadata, intelligent automation, and production-grade AI systems.

We believe AI does not scale on data alone. It scales on trusted context.

Context66 combines deep architecture expertise, hands-on engineering, AI-native delivery, and reusable accelerators to help organizations simplify complexity, modernize platforms, improve data trust, and move AI from experimentation into measurable enterprise outcomes.

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.
- Robust 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, Databricks, 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.

📌 Data Engineer (Mumbai)
🏢 Kalpavruksh Systems
📍 Mumbai