Data Analytics/Engineer (Python and MS Fabric exp)

Soft Skills :

• Strong analytical skills; capable of multi-tasking in fast-paced, dynamic environment
• Strong written and verbal communication, including report writing and data storytelling
• Stay updated with industry trends and evolving tools; Demonstrate a proactive approach to learning new techniques and technologies
• Work effectively across cross-functional teams
• Strong stakeholder management and ability to translate business needs into technical solutions.
• Experience presenting technical concepts to non-technical audiences.
• Proven ability to lead cross-functional initiatives and drive consensus.

ESSENTIAL DUTIES

Model Development & Deployment:

• Develop predictive models to forecast key sales and marketing metrics solve to complex business problems and drive strategic insights.
• Lead the end-to-end lifecycle of data science projects, including data preparation, feature engineering, model development, validation, and deployment.
• Lead and architect predictive modeling frameworks.
• Review and guide model development by junior team members.
• Design and implement scalable analytics platforms.
• Drive strategic data initiatives in collaboration with finance and business leaders.

Data Analysis & Insights:

• Analyze large, complex datasets from multiple sources to identify trends, patterns, and opportunities that inform decision-making.
• Collaborate with finance and accounting teams to automate reconciliations, variance analysis, and error detection using advanced analytics and machine learning.

Innovation, Automation & Generative AI:

• Lead initiatives leveraging Generative AI (GenAI) technologies to automate the generation of financial reports, narratives, and data summaries, enhancing efficiency and accuracy.
• Lead GenAI strategy for data engineering and analytics automation.
• Evaluate and implement emerging technologies to enhance data workflows.
• Explore and implement GenAI applications to improve natural language processing (NLP) capabilities for extracting insights from unstructured financial documents (e.g., contracts, invoices).
• Drive the adoption of GenAI-powered chatbots or virtual assistants to support finance shared services teams with data queries, process guidance, and routine task automation.

OTHER DUTIES

Support Data Infrastructure & Governance:

• Lead efforts to design, optimize, and scale data infrastructure in Microsoft Fabric, defining clear data requirements and overseeing robust ETL/ELT processes.
• Drive data governance initiatives by implementing data quality frameworks, ensuring thorough documentation, and standardizing practices across teams to maintain data integrity.

Enhance Reporting & Analytics Standards:

• Collaborate with analytics and BI teams to establish dashboard design standards, improve user experience, and ensure consistent KPI definitions across the organization.

Promote a Data-Driven Culture:

• Advocate for a data-driven culture, promoting the value of analytics in strategic and operational decision-making.
• Lead or support analytical training sessions or workshops for non-technical stakeholders to improve data literacy across the organization.

Cross-Functional Collaboration:

• Partner with business, product, and operational teams to provide expert data engineering support, enabling effective data-driven solutions and innovation across departments.

Our Interview Practices

To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you—not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.

Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.