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Job Profile: Data Scientist (ETL Engineer – Azure, Power BI, Python)
Client: Lufthansa Technik (Onsite – Client Office)
Mandatory Skills
- ETL Engineering
- Azure Synapse Analytics
- Power BI
- Python
Role Summary
We are looking for a Data Scientist to design, develop, and deliver end-to-end analytics solutions in the Finance domain. The role requires expertise in Python, ETL pipelines, Azure data analytics toolsets, and dashboarding solutions. You will work closely with Data Engineers and ML Engineers to ensure seamless delivery of advanced analytics projects and automation of AI/ML workflows.
Key Responsibilities
Project Delivery & Collaboration
- Deliver advanced analytics and data science projects within scope, time, and budget.
- Collaborate with Data & ML Engineers to understand data and model requirements.
- Translate business needs into scalable technical solutions.
Data Science & Analytics
- Develop solutions using Python, statistics, and machine learning techniques.
- Perform end-to-end pipeline management: problem scoping, data preparation, modeling, visualization, monitoring, and maintenance.
- Build predictive models, time-series forecasts, regression/classification solutions.
Visualization & Reporting
- Design interactive dashboards in Power BI, Python Dash (Plotly), or Flask.
- Create data stories for business users through effective visualization.
ETL & Data Management
- Build and maintain ETL pipelines in SAP Data Sphere and integrate with Power BI / SAP Analytics Cloud.
- Manage data procurement, processing, and integration strategies.
Technology & Innovation
- Work with Azure Synapse Analytics, Azure ML, and CI/CD pipelines.
- Troubleshoot and monitor data platform infrastructure (alerts, logs, dashboards).
- Explore and apply emerging technologies like GenAI and Agentic AI.
Technical Expertise Required
- Strong skills in Python and libraries: Pandas, PySpark, Scikit-Learn, TensorFlow, Keras, PyTorch, etc.
- Solid understanding of Statistics & Probability.
- Hands-on experience in Finance domain projects.
- Experience with SAP Data Sphere, Power BI, and SAC.
- Working knowledge of DevOps/MLOps in Azure.
- Strong problem-solving, analytical, and communication skills.
Qualifications
- Bachelor's/Master's in Computer Science or related field.
- 3–5 years of professional experience.
- Minimum 3 years in Data Science / ML / AI.
- At least 2 years in Finance domain (preferred).
- Proven experience with ETL pipelines and dashboarding.
Location: Onsite – Client Office (Lufthansa Technik)
Experience: 3 to 5 years
Domain: Finance / Data Analytics
