Full Stack Data Engineer(DataBricks & ML)

Full Stack DE Expert

Location: Remote

Experience: 8+ Years

Company Overview

Codvo is a global empathy-led technology services company where software engineering excellence and human-centered innovation come together. Our mission is to accelerate our clients digital transformation through world-class design, cloud engineering, data modernization, digital engineering, and enterprise AI.

As we deepen our focus on the Oil & Gas sector, we partner with upstream, midstream, downstream, LNG, chemical, and pipeline operators to unlock measurable value across their digital and AI transformation journeys.

• Design, build, and maintain Databricks data pipelines (ETL/ELT) for ingestion, transformation, and orchestration using Spark/Delta Lake/Databricks Workflows. • Must have practical experience in Databricks and MLflow, including model development, experiment tracking, model management, and deployment in a production environment.
• Operationalize machine learning models by building inference pipelines that invoke models authored by data scientists (batch or real-time), ensuring consistency between training and inference environments.
• Ensure data reliability, quality, and observability through robust validation, monitoring, alerting, and automated recovery mechanisms.
• Collaborate closely with data scientists to productionize models, manage model deployment lifecycles, and optimize inference performance and cost.
• Implement best-practice DevOps/MLOps processes such as CI/CD for pipelines, model versioning, environment promotion, and infrastructure-as-code.
• Optimize performance and cost across compute clusters, jobs, and storage layers.
• Implement and manage the enterprise data catalog, including schema design, table ownership, lineage, governance, and documentation using Unity Catalog.
• Experience with some Databricks infrastructure.
• Experience with building BI dashboards and visualization.
• Experience with coding agents and best practices (spec-driven development, etc.).

Must Have:

• Databricks platform experience
• Python development for data processing and ETL pipelines
• Unity Catalog knowledge
• AWS data services (S3, IAM, VPC, potentially Glue/Lambda)
• Data lake/lakehouse architecture patterns
• Dashboard building experience

Nice to Have:

• RESTful API design and development (Flask, FastAPI, or similar)
• Authentication/authorization patterns (OAuth, API keys, IAM roles)
• Query optimization and performance tuning
• PySpark optimization experience
• ML/AI pipeline experience
• Databricks AI/BI