Meaningful work,
meaningful life

Qualifications:

• Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related field.

• 8+ years of experience in data engineering, with a focus on scalable architecture design.

• Strong proficiency in Python, PySpark, Python-based UI libraries and Gradio or Streamlit.

• Strong proficiency in Python, especially in Pandas and NumPy.

• Strong proficiency in Databricks environment and Native Apps

• Hands-on experience with Databricks (notebooks, jobs, lakehouse architecture).

• Experience building charts and dashboards using Matplotlib, Seaborn, or Plotly.

• Experience in python webapp and rest API development

• Good to have understanding of SAS (PROC steps, data handling, stored processes).

• Understanding of data structures, statistical methods, and basic analytical modeling.

• Good understanding of cloud data architecture and deployment best practices.

JD:

• Analyze existing SAS web-based forecasting and reporting applications.

• Convert SAS stored processes and PROC logic into PySpark equivalent Native Apps.

• Translate SAS data handlers and preprocessing routines to Python-based scripts.

• Rewrite forecasting logic and model calculations in Python.

• Develop interactive dashboards using Python + Matplotlib/Plotly

• Design and deploy user-friendly Apps for real-time interaction with data and forecasting outputs.

• Package and deploy the final application within the Databricks App environment.

• Collaborate with business SMEs to understand requirements and ensure functional parity with legacy SAS systems.