Data Analytics/Engineer (Python and MS Fabric exp)
Wolters Kluwer (company site, opens in a new tab)5+ yrsPuneOn-siteDirect career pageEst. 15–28 LPA
Posted on 21 Sept
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Job description
Structured overview of role & requirements
About This Role
- Lead design, development, and deployment of scalable data analytics and predictive modeling solutions using Python, SQL, and Microsoft Fabric.
- Drive implementation of Generative AI initiatives to automate financial reporting, NLP on unstructured data, and workflow enhancements.
- Oversee data infrastructure optimization, governance, and collaborate cross-functionally to enable data-driven decision-making and analytics innovation.
Minimum Requirements
- Bachelor’s degree in data science, analytics, computer science, or related quantitative field; Master’s degree preferred.
- Minimum 5+ years experience in data analytics or data engineering roles with leadership or mentorship responsibilities.
- Proficiency in Python/PySpark, SQL, Microsoft Fabric, and cloud data platforms such as AWS or Fabric.
- Experience with data pipeline tools (e.g., Apache Airflow, dbt, Azure Data Factory, Informatica) and familiarity with CI/CD and DevOps practices.
Ideal Candidate Profile
- Experienced data engineer or analytics lead with strong expertise in architecting scalable cloud-based data platforms and pipelines, particularly using Microsoft Fabric and AWS.
- Proven track record of leading AI/ML driven automation projects, particularly with Generative AI applied to finance and unstructured data analytics.
- Skilled in managing cross-functional initiatives, driving data governance, and translating complex technical concepts for non-technical stakeholders.