About the role

Profile : Senior Data Engineer

Keywords :

Azure Databricks, PowerBI, Azure Datafactory (ADF), Data Transformation, Automating Reports, Azure Worfklow & pipelines, AI based Reports.

Primary Responsibilities:

Morning Stand-Up: Participate in daily stand-up meetings to discuss progress, blockers, and plans for the day
Code Development in Python/Java: Write, test, and maintain high-quality code using defined programming languages and frameworks
Modify queries to generate appropriate Dashboards in Azure Databricks, PowerBI, Tableau or Custom UI based on business requirements
Code Reviews: Conduct and participate in code reviews to ensure code quality and share knowledge with team members
Collaboration: Work closely with cross-functional teams, including product managers, designers, and other engineers, to deliver robust software solutions
Problem Solving: Troubleshoot and debug issues in a timely manner, ensuring minimal disruption to the development process
Continuous Learning: Stay updated with the latest industry trends, technologies, and best practices to continuously improve skills and knowledge
Documentation: Create and maintain comprehensive documentation for code, APIs, and system architecture. Document technical specifications and contribute to knowledge sharing within the team.
Testing: Develop and execute unit tests, integration tests, and automated tests to ensure software reliability and performance. Write unit and integration tests to ensure code quality and reliability
Deployment: Participate in the deployment process, ensuring smooth and efficient releases
Analyzes and investigates
Provides explanations and interpretations within area of expertise
Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so
Collaborate with cross-functional teams including QA, Product Management, and DevOps.

Qualifications - Internal

Required Qualifications:

Undergraduate degree or equivalent experience
6-9 years of experience in the industry
Experience with cloud platforms such as Azure, AWS or Google Cloud
Experience in Reporting, Data Analytics and engineering using Python, PySpark and Spark SQL for large‑scale data.
Strong SQL and Python expertise for complex joins, aggregations, deduplication, and performance tuning on claims data
CI/CD Pipelines: Experience with continuous integration and continuous deployment (CI/CD) tools and practices. End‑to‑end data pipeline development using Azure Data Factory (ADF), including parameterization and error handling.
Secure data handling using enterprise standards (Key Vault, managed identities, privileged access, HIPAA awareness)
Version Control: Solid understanding of version control systems, particularly Git
Authentication/Authorization: Knowledge of OAuth 2.0, SAML, and OpenID Connect for secure authentication and authorization
Database Management: Proficiency in working with relational and NoSQL databases like Oracle, MySQL, PostgreSQL, MongoDB, or CosmosDB
Agile Methodologies: Familiarity with Agile development methodologies such as Scrum or Kanban
Problem-Solving Skills: Proven excellent analytical and problem-solving abilities
Understanding of object-oriented programming, data structures, and algorithms.

Good-to-Have Qualifications (API Development / AI / Intelligent Systems):

API Development: Experience in designing and developing RESTful and/or GraphQL APIs
Proficiency in Modern Programming Languages: Solid experience with languages such as Java, Angular, Javascript, React JS, Node JS
Web Development: Solid understanding of front-end and back-end web development technologies, including HTML, CSS, and frameworks like React or Angular, Bootstrap
Experience integrating AI/ML capabilities into enterprise applications
Familiarity with Generative AI concepts and frameworks (e.g., LLMs, prompt engineering, embeddings)
Hands-on exposure to AI services such as Azure OpenAI, Azure AI Services, AWS Bedrock, or Google Vertex AI
Understanding of Responsible AI principles, including data privacy, security, bias, and model governance.
Experience building or consuming AI-powered APIs (chatbots, copilots, recommendations, summarization, etc.)
Knowledge of vector databases and semantic search technologies
Ability to evaluate AI use cases for feasibility, scalability, and business value
Familiarity with MLOps concepts, model lifecycle management, or AI observability is a plus.