Full Stack / Data Platform Developer

The team is seeking a hands-on Full Stack / Data Platform Developer to support the development of AI-enabled enterprise solutions. This role involves owning key elements of the backend, data pipelines, cloud environment, and application integration, while collaborating closely with Data Scientists, AI Engineers, and business teams to transition solutions from sandbox development to scalable deployment.

Key responsibilities include:

• Design and build end-to-end data pipelines connecting enterprise source systems, data lakes/lakehouses, analytical databases, AI models, and front-end applications.
• Develop and maintain ETL/ELT pipelines for structured and semi-structured enterprise data using Python, SQL, and relevant AWS services.
• Set up and manage Bronze–Silver–Gold / Medallion architecture, including raw, cleansed, harmonized, and consumption-ready datasets.
• Build backend services and REST APIs to expose data, model outputs, and recommendations to front-end applications.
• Support ingestion from enterprise systems such as ERP, procurement platforms, databases, APIs, Excel/files, and document repositories.
• Implement data-quality checks, schema validation, data lineage, metadata management, and appropriate data-governance controls.
• Collaborate with Data Scientists / AI Engineers to create AI-ready datasets, feature pipelines, and model-serving interfaces.
• Support AWS infrastructure connectivity for data, including compute, storage, databases, networking, and access configuration.
• Provision and configure VMs / EC2 instances and development environments required for AI and application workloads.
• Containerize applications and services using Docker and support CI/CD-based movement across development, UAT, and production environments.
• Work with client IT teams and technology partners to ensure solutions developed in sandbox environments can be deployed reliably into the team production architecture.
• Support logging, monitoring, security, RBAC, and troubleshooting across the application and data stack.

The ideal candidate will possess the following technical skills:

• Core: Python, SQL, REST APIs, Git, Docker, data modeling, ETL/ELT, and backend development.
• AWS: Hands-on experience with services such as S3, EC2, IAM, RDS/Aurora, Lambda, Glue, Athena, API Gateway, and CloudWatch; exposure to Redshift, EMR, EKS/ECS, or SageMaker is advantageous.
• Data engineering: Understanding of data lakes/lakehouses, Medallion architecture, Parquet/Delta formats, master/reference data, data quality, lineage, and data governance.
• Application: Experience building backend services using frameworks such as FastAPI, Flask, Django, or Node.js. Ability to work with a front-end framework such as React is advantageous.
• DevOps: Familiarity with CI/CD, environment management, infrastructure configuration, secrets management, and production deployment.

Candidates should have 4-5 years of hands-on software/data engineering experience, having built applications involving the complete flow from source to data pipeline, database/lakehouse, analytics/AI, API, and user application. The ideal profile includes strong problem-solving and debugging capabilities, a dynamic and self-driven attitude, and a willingness to learn new technologies quickly. Comfort working in an agile environment with business users, Data Scientists, architects, and client IT teams is essential.

What we offer:

• A collaborative and innovative work environment.
• Opportunities for professional growth and development.
• The chance to work on cutting-edge AI and data solutions.