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Job Description
Structured overview of role & requirementsAbout This Role
Lead architecture, design, and evolution of scalable, cloud-native data backend systems and APIs focusing on Databricks lakehouse platform.
Own end-to-end development, deployment, and operational excellence of Python-based API services, relational database schemas, and CI/CD pipelines.
Collaborate cross-functionally with architects, data scientists, engineers, and SRE teams to deliver high-performance, cost-efficient analytics and AI/ML solutions.
Minimum Requirements
Bachelor's or master's degree in Computer Science, Engineering, or equivalent experience.
8+ years of backend engineering experience with strong expertise in Python application/service development and API ownership (FastAPI, Flask).
Strong RDBMS experience with PostgreSQL including schema design, query optimization, and migration tooling; CI/CD pipeline ownership (GitHub Actions, Terraform).
Experience with cloud platforms (preferably AWS ECS/Fargate, RDS, S3), cloud-native architectures, infrastructure as code, and data or analytics platform development.
Ideal Candidate Profile
Deep expertise in Databricks and modern distributed data engineering platforms, with hands-on experience in lakehouse architectures.
Proven ability to lead complex backend initiatives end-to-end including technical strategy for reliability, scalability, and cost efficiency.
Experience with enterprise SaaS, FinOps, cloud cost optimization, and AI-powered backend systems including LLM-based workflows is strongly preferred.