Fullstack Data Engineer (India) (Remote)
Job Description : Data Engineer
Role Overview
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.
Key Responsibilities
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).
Required Skills & Qualifications
Core Databricks Skills:
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
Programming & Full Stack:
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.
Cloud Platforms:
Proficiency with at least one: Azure Databricks, AWS Databricks, or GCP Databricks.
Knowledge of cloud storage (ADLS, S3, GCS), IAM, networking.
DevOps & CI/CD:
Git, CI/CD tools (GitHub Actions, Azure DevOps, Jenkins).
Containerization (Docker, Kubernetes is a plus).
Data Engineering Foundations:
Data modeling (OLTP/OLAP).
Batch & streaming data processing (Kafka, Event Hub, Kinesis).
Data governance & compliance (Unity Catalog, Lakehouse security).
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
Qualifications
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.
Soft Skills
Strong problem-solving and analytical skills.
Ability to work in fusion teams (business + engineering + AI/ML).
Clear communication and documentation abilities.
About Us
At Codvo, we are committed to building scalable, future-ready data platforms that power business impact. We believe in a culture of innovation, collaboration, and growth, where engineers can experiment, learn, and thrive. Join us to be part of a team that solves complex data challenges with creativity and cutting-edge technology.
