Senior Data Analytics Engineer

ABOUT US Wolters Kluwer is a global leader in professional information services that combines deep domain knowledge with specialized technology. Our portfolio offers software tools coupled with content and services that customers need to make decisions with confidence. Every day, our customers make critical decisions to help save lives, improve the way we do business, build better judicial and regulatory systems. We help them get it right. JOB QUALIFICATIONS Education : Bachelor s degree in data science/analytics or Engineering in Computer Science, or related quantitative field. Master s degree preferred. Experience : 5+ years of hands-on experience in data analysis, business intelligence, or a related analytics role. Proven track record of leading analytical initiatives, building and deploying AI/ML models, and delivering enterprise-grade dashboards to senior leadership. Demonstrated experience mentoring junior analysts and guiding cross-functional data projects. Technical Skills : Strong proficiency in Python for data manipulation (Pandas, NumPy), statistical analysis (SciPy, Stats models), visualization (Matplotlib, Seaborn, Plotly), and end-to-end automation of analytical workflows. Experience with PySpark for large-scale data processing is a plus. Expert-level skills in Power BI (DAX, Power Query, data modeling) and/or Tableau. Proven ability to architect enterprise-wide dashboard frameworks, establish design standards, ensure consistent KPI definitions, and drive adoption across stakeholder groups. Extensive hands-on experience building, validating, and deploying predictive, classification, and clustering models using frameworks such as Scikit-learn, XGBoost, TensorFlow, or PyTorch. Strong command of feature engineering, hyperparameter tuning, model evaluation, and production deployment strategies. Experience with GenAI tools and frameworks (e.g., LangChain, OpenAI APIs, Azure OpenAI) for automating report generation, NLP-based insight extraction from unstructured data, or chatbot-driven analytics support. Advanced SQL skills for querying complex datasets across multiple sources. Strong understanding of data modeling, schema design, performance tuning, and data quality principles. Familiarity with Microsoft Fabric and its integration within modern data ecosystems, Azure Data Factory, or similar cloud-based platforms. Knowledge of Git, CI/CD pipelines, and DevOps practices for reproducible and scalable analytical workflows. Background in finance domain is a plus. 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 Dashboard Architecture Visualization Leadership: Architect, build, and maintain enterprise-grade interactive dashboards in Power BI that provide real-time visibility into key business metrics across sales, marketing, and finance functions. Establish and enforce dashboard design standards, improve user experience, and ensure consistent KPI definitions across the organization. Automate recurring reporting workflows using Python scripts or Fabric Data flows integrated with BI tools to reduce manual effort, improve accuracy, and scale reporting capabilities. Design and implement scalable analytics platforms that serve as a single source of truth for organizational metrics. Data Analysis Strategic Insights: Analyze large, complex datasets from multiple sources to identify trends, patterns, and opportunities that inform strategic decision-making. Collaborate with finance and accounting teams to automate reconciliations, variance analysis, and error detection using advanced analytics and machine learning. Lead deep-dive analyses on key sales, marketing, and financial metrics, translating findings into actionable recommendations for senior leadership. Review and guide analytical work produced by junior team members, ensuring quality, accuracy, and alignment with business objectives Innovation, Automation Generative AI: Automate financial reporting and narrative generation. Extract insights from unstructured documents Build chatbots/assistants for finance teams Implement agentic AI/workflow automation OTHER DUTIES Support Data Infrastructure Governance: Collaborate with data engineering teams to ensure data availability, quality, and accessibility for advanced analytics and modeling. Participate in data governance initiatives by validating data integrity, documenting data sources, and standardizing datasets for consistent use .