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.

Job Description • 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