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Codvo AI · IT - Software Development

Fullstack Data Engineer

India · Job Posted June 03, 2026
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Job Description

We are looking for a highly skilled Full Stack Data Engineer with expertise in data technologies like snowflake, Azure Data Factory, Databricks to design, develop, and optimize end-to-end data pipelines, data platforms, and analytics solutions. This role combines strong data engineering, cloud platform expertise, and software engineering skills to deliver scalable, production-grade solutions.

Job Responsibility

  • Design and develop ETL/ELT pipelines on platforms like Databricks (PySpark, Delta Lake, SQL), Informatica, Teradata, Snowflake
  • Architect data models (batch and streaming) for analytics, ML, and reporting
  • Optimize performance of large-scale distributed data processing jobs
  • Implement CI/CD pipelines for Databricks workflows using GitHub Actions, Azure DevOps, or similar
  • Build and maintain APIs, dashboards, or applications that consume processed data (full-stack aspect)
  • Collaborate with data scientists, analysts, and business stakeholders to deliver solutions
  • Ensure data quality, lineage, governance, and security compliance
  • Deploy solutions across cloud environments (Azure, AWS, or GCP)

Requirements

  • Strong in PySpark, Delta Lake, Databricks SQL
  • Experience with Databricks Workflows, Unity Catalog, and Delta Live Tables
  • Experience in snowflake, data engineering technologies like ETL, ELT
  • Python (mandatory), SQL (expert)
  • Exposure to Java/Scala (for Spark jobs)
  • Knowledge of APIs, microservices (FastAPI/Flask), or basic front-end (React/Angular) is a plus
  • Proficiency with at least one: Azure Databricks, AWS Databricks, or GCP Databricks
  • Knowledge of cloud storage (ADLS, S3, GCS), IAM, networking
  • Git, CI/CD tools (GitHub Actions, Azure DevOps, Jenkins)
  • Containerization (Docker, Kubernetes is a plus)
  • Data modeling (OLTP/OLAP)
  • Batch & streaming data processing (Kafka, Event Hub, Kinesis)
  • Data governance & compliance (Unity Catalog, Lakehouse security)
  • Bachelor’s or Master’s in Computer Science, Data Engineering, or related field
  • 4–7 years of experience in data engineering, with deep expertise in Databricks
  • Strong problem-solving and analytical skills
  • Ability to work in fusion teams (business + engineering + AI/ML)
  • Clear communication and documentation abilities

Nice to have

  • Experience with machine learning pipelines (MLflow, Feature Store)
  • Knowledge of data visualization tools (Power BI, Tableau, Looker)
  • Exposure to Graph databases (Neo4j) or RAG/LLM pipelines
  • Experience working in Informatica, Teradata in ETL, ELT
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