Description :

We are looking for a hands on Data Engineer/AI Developer who can rapidly build AI enabled applications, automate workflows, and deliver solutions end to end using modern SDLC practices.

The role requires a builder mindset someone comfortable moving from idea to prototype to production quickly, while following good engineering discipline.

Key Responsibilities :

- Build lightweight data & AI applications (dashboards, APIs, copilots, automations, PoCs)

- Develop data pipelines, feature flows, and AI integrations (batch & near/real/time)

- Implement automation and workflows across systems (APIs, event?driven, scheduled jobs)

- Apply SDLC best practices: version control, CI/CD, testing, documentation

- Collaborate with business and product teams to translate ideas into working solutions

- Package solutions for reusability and scale (modular code, templates, configs)

- Stay current with new techniques, tools, and frameworks in data science and AI

Functional & Business Competencies :

- Machine Learning & Model Development

- Statistical Analysis & Feature Engineering

- Problem Framing & Hypothesis Testing

- Business Impact Orientation

- Collaboration with Engineering & Product Teams

- Data Pipeline Design & Optimization

- ETL/ELT Development

- Cloud Data Services

- Collaboration with Analysts & Scientists

- Data Quality & Performance Monitoring

- Clear Communication of Analytical Findings

Qualifications & Experience :

- 5 to 7 years of experience in data science, machine learning, or applied statistics

- Hands on experience in application development and workflows.

- Proficient in Python (e.g., scikit-learn, pandas), SQL, and ML frameworks

- Familiarity with cloud services for data (e.g., Databricks, Azure Data Factory)

- Experience working with cloud-based ML environments (AWS Sagemaker, Azure ML, etc.)

- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or related field