Azure Databricks Engineer

Infosys

About The Position

The Azure Databricks Engineer will work in Infosys’s Data and Analytics (DNA) unit, which develops data, AI, and analytics solutions for business challenges. In the assigned role of Technology Consultant 2, the position contributes across the software development lifecycle, from requirements elicitation and design through implementation, testing, production support, and documentation. The work includes architecting and implementing data solutions with Microsoft Azure, Azure Databricks, and Azure Data Factory, as well as building scalable distributed data systems and data warehouses or marts. The role also involves collaboration with cross-functional teams, technical leadership and mentoring, and maintaining software quality and system reliability. Relocation and/or travel to the work or project location may be required. Infosys cannot provide immigration sponsorship for this role; applicants must be authorized to work in the United States without employer-based visa sponsorship.

Requirements

Experience architecting and implementing data solutions using Microsoft Azure, Azure Databricks, and Azure Data Factory (ADF).
Proficiency in Apache Spark, Kafka, SQL, and Python.
Hands-on experience implementing data warehouses and data marts end to end.
Understanding of data warehousing concepts, including Data Vault, dimensional modeling, and OLAP design.
Experience designing and implementing scalable solutions for distributed data systems.
Hands-on experience with CI/CD pipelines and platforms such as GitHub Actions and Azure Pipelines.
Experience leading technical teams and mentoring data engineers.
Problem-solving skills and the ability to design and deliver complex data engineering solutions.
Bachelor’s degree or foreign equivalent from an accredited institution, or three years of progressive experience in the specialty in lieu of each year of education.
Authorization to work in the United States for any employer without employer-based visa sponsorship.

Nice To Haves

Understanding of retail data domains and related use cases.
Familiarity with vector search and semantic retrieval, preferably for retail use cases.
Experience with relational modeling, dimensional modeling, and modeling unstructured data.
Familiarity with logging, monitoring, and observability solutions.
Experience with development containers, unit testing, code-quality reviews, and linting.
Understanding of Agile software development methodologies.
Ability to work effectively in a diverse, multi-stakeholder environment across business and technology teams.
Experience working in a global delivery environment.
Experience implementing automation capabilities within data engineering or development processes.
Exposure to Generative AI frameworks and technologies such as OpenAI, Hugging Face, and LangChain.

Responsibilities

Document assigned portions of business requirements as part of requirements elicitation.
Facilitate software application design discussions and document design decisions for the technical team.
Participate in coding and integrate features or updates into existing applications while maintaining system stability.
Conduct code reviews, make codebase changes, and maintain code repositories.
Implement test strategies, analyze results, and coordinate bug fixes to uphold software quality standards.
Develop user training programs, documentation, and support frameworks for transitions to new software applications.
Resolve production issues and recommend preventive strategies to enhance system reliability.
Maintain detailed records of code, testing techniques, and support activities.
Contribute across end-to-end SDLC phases, from requirements gathering through implementation.
Work with cross-functional teams on software integration.
Lead technical teams and mentor data engineers.