Job Description:
Data Engineer – Databricks
Role Overview
We are looking for a highly skilled Full Stack Data Engineer with expertise in 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 Databricks (PySpark, Delta Lake, SQL).
- 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.
Required Skills & Qualifications
- Core Databricks Skills:
- Strong in PySpark, Delta Lake, Databricks SQL.
- Experience with Databricks Workflows, Unity Catalog, and Delta Live Tables.
- 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.
Qualifications
- Bachelor’s or Master’s in Computer Science, Data Engineering, or related field.
- 4–7 years of experience in data engineering, with at least 2 years on 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.