Azure Data Engineer
2 weeks ago
ROLES & RESPONSIBILITIES
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.
EXPERIENCE
8-11 Years
SKILLS
Primary Skill: Data Engineering
Sub Skill(s): Data Engineering
Additional Skill(s): Python, ETL, databricks, Azure Data Factory, Pyspark
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