Data Engineer

🚀 Project Overview
This role focuses on designing and developing integrated data analytics and automation solutions by extracting and transforming data from engineering platforms such as SDOM, ALM, and Jira. The objective is to enable data‑driven decision making, process optimization, and intelligent automation through advanced analytics, dashboards, and AI‑driven applications.
The role plays a key part in building scalable solutions that combine data engineering, low‑code/no‑code platforms, and Generative AI capabilities to improve engineering productivity and reporting efficiency across teams.
🔑 Key Responsibilities
1️⃣ Data Integration & Analytics
Extract, consolidate, and transform data from multiple engineering tools (SDOM, ALM, Jira).
Perform data analysis to identify trends, bottlenecks, and improvement opportunities.
Ensure data quality, consistency, and reliability across reporting systems.
2️⃣ Dashboard & Reporting Solutions
Design and develop interactive dashboards using Power BI and custom reporting tools.
Build real‑time and periodic reporting frameworks to track KPIs and performance metrics.
3️⃣ Application Development (Low‑Code / No‑Code)
Develop business applications using Power Apps and SharePoint List‑based applications.
Create user‑friendly interfaces for data interaction, reporting, and workflow tracking.
4️⃣ Automation Solutions
Design and implement workflows using Power Automate.
Automate data collection, report generation, and notifications.
Improve process efficiency by reducing manual effort.
5️⃣ Advanced Scripting & Development
Develop Python scripts for data extraction, transformation, automation, and custom analytics.
Integrate scripts with dashboards and automation pipelines.
6️⃣ Generative AI & Prompt Engineering
Design and optimize prompts for Large Language Models (LLMs).
Build AI‑assisted solutions for data insights generation, report summarization, and intelligent query handling.
7️⃣ Training & Knowledge Solutions
Develop and maintain training dashboard applications.
Track user adoption, learning progress, and skill development metrics.
Enable self‑service learning and reporting.

Work arrangement
No