Data Engineer_ExpertJob Description • Design, build, and maintain Databricks data pipelines (ETL/ELT) for ingestion, transformation, and orchestration using Spark/Delta Lake/Databricks Workflows. • 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 / Nice to Have Skills Required: • 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
Pay: ₹252,509.00 - ₹3,883,391.88 per year
Benefits:
Application Question(s):
- Notice period
- Current CTC
- expected CTC
Experience:
- Data engineer: 5 years (Required)
- Total : 6 years (Required)
- Databricks: 4 years (Required)
Work Location: Hybrid remote in Pune, Maharashtra (Pune, Pune District)
