Join our dynamic team as a Technical Specialist focusing on Data Engineering. This role is integral to our FP&A Reporting Automation & AI Forecasting program, where you will build robust Python modules for various data processing tasks.

You will be instrumental in developing backend services and Azure Function-based pipelines, ensuring seamless data flow from Excel uploads to our databases. This position requires a strong understanding of Python, Excel handling, API development, and DevOps practices.

We are seeking a collaborative individual who can work effectively in an Agile environment and contribute to the operationalization of machine learning models. Your expertise will help us enhance pipeline resilience and performance, supporting critical financial reporting and forecasting initiatives.

Design and implement production-grade Python modules for ingesting Excel files, parsing templates, and transforming/consolidating datasets.

Develop backend services and APIs, leveraging Azure Functions, to migrate data from Excel uploads (via SharePoint/ADLS) into databases for downstream reporting.

Integrate business rules, exception reporting logic, version control, and audit trails according to technical designs.

Write clear, well-documented, and thoroughly tested code, actively participating in peer code reviews.

Collaborate with Data Scientists to deploy ML models, creating inference APIs, batch scoring jobs, and data persistence layers.

Troubleshoot production issues, provide hypercare support during go-live phases, and continuously optimize pipeline performance and resilience.

Possess a strong foundation in Python (4+ years), including proficiency with Python 3.10+, pandas, NumPy, and standard libraries, emphasizing OOP and modular design principles.

Demonstrate solid experience with Excel handling libraries such as openpyxl, pandas, xlrd/xlwings, and navigating complex Excel structures.

Exhibit expertise in building APIs using FastAPI or Flask, and experience consuming REST APIs, alongside developing Streamlit applications.

Be proficient with version control systems like Git, including branching strategies and pull requests, and have experience with CI/CD pipelines (Azure DevOps or GitHub Actions).

Showcase practical knowledge of testing frameworks like pytest and familiarity with unit and integration testing methodologies.

Thrive in an Agile setting, comfortable with Scrum sprints, story estimation, and tools like JIRA or Azure Boards.

Familiarity with Finance/FP&A concepts and Excel-heavy workflows is a significant advantage, as is exposure to Streamlit/Plotly Dash for dashboards. Basic understanding of ML model integration is also beneficial.