Data Engineer | 4 to 6years | Bengaluru
Capgemini
Job Description
Data Engineer Description:
Degree and Qualification:
• BE/B.Tech, ME/M.Tech in CSE/IT, Statistics, or a related field.
• Master’s degree in data science, AI, or a related field is preferred.
Number of Years of Experience as a Data Analyst / Scientist: 3-8 years
Language Skills:
• Good communication skills in English, proficiency in German is an added advantage.
Domain Knowledge:
• Strong understanding of supply chain and supplier performance evaluation processes.
• Familiarity with procurement, supplier management, inbound processes, and logistics concepts like goods receipt, delivery note, and part numbers.
• Basic knowledge of plant logistics and operational efficiency.
Technical Skills: Python, PySpark, SQL, Power BI (Advanced Level), Databricks, Azure/AWS, Machine Learning, Data Visualization, TensorFlow, PyTorch, and deploying ML models in production.
Digital Expertise:
1. Power BI Desktop (advanced):
o Advanced knowledge of building dashboards, creating data models, and writing DAX expressions,
o Ability to develop custom visualizations in Power BI using Python scripts / other suitable methods to create charts and data representations not supported natively by Power BI
o Ability to write Python scripts to process and transform data within Power Query for advanced analytics and visualization scenarios.
o Strong design / Power BI UI/ UX skills to ensure Power BI dashboards aligns with business objectives and effectively tells a data-driven story.
o Power BI Service (advanced):: Experience in publishing, refreshing, and managing reports in Power BI Service, including RLS and data gateways.
2. Machine Learning & AI:
o Experience in building predictive models using machine learning algorithms such as regression, classification, clustering, and anomaly detection.
o Familiarity with AI concepts like neural networks, NLP, or reinforcement learning.
3. Data Wrangling & Analysis:
o Proficiency in Python and popular data libraries like Pandas, NumPy, and Scikit-learn.
o Experience in PySpark for distributed data processing and large-scale data transformation.
o Strong SQL skills for querying relational databases, optimizing queries, and handling complex datasets.
4. Communication & Stakeholder Management:
o Ability to effectively communicate technical insights to non-technical stakeholders.
o Strong customer-facing communication skills and experience collaborating with cross-functional teams.
Behavioral / Personal Skills:
• Willingness to learn and apply new skills.
• High adaptability and readiness to handle unstructured tasks.
• Strong analytical mindset, with a focus on problem-solving and result-oriented thinking.
• Team player with excellent communication and interpersonal skills.