Job description

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.

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