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    Job · 21764881

    REMOTEFULLTIME

    Data Engineer

    Kalpavruksh Systems logo

    Kalpavruksh Systems

    Remote · remote · Posted 1d ago

    Sourced fromNaukri
    Undisclosed4–8 yrsfulltimeRemote

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    Section · 01

    About this role

    Job Description

    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.
    • 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, 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.

    Sourced from naukri

    Section · 02

    Skills

    amazon web servicesData Platform ArchitectureDatabricksPythonMicrosoft AzureData Modeling

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