Senior Data Analytics Engineer (5+ years only with Python, Power BI, SQL)
Wolters Kluwer is hiring a Senior Data Analytics Engineer (5+ years only with Python, Power BI, SQL) in Pune, India. Level rates it ; you can apply on Level.
AI in this role
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 across projects.
Enhance Reporting & Analytics Standards:
- Contribute to the development of analytics frameworks, dashboards, and reporting tools that translate complex models into actionable business insights.
- Work closely with BI teams to refine KPI definitions and improve visualization standards for clearer communication of analytical results.
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:
- Collaborate on cross-functional initiatives, applying AI-driven solutions, machine learning, and data analytics to support business objectives.
TRAVEL REQUIREMENTS
Minimal travel might be required.
PHYSICAL DEMANDS
Pune office on a hybrid schedule (Mondays and Tuesdays).
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.
How we rate this
Senior Data Analytics Engineer (5+ years only with Python, Power BI, SQL) at Wolters Kluwer rates 63 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide that one model's output is better than another's for a given task?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- What are the limits of OpenAI that you've run into, and how did you work around them?
- What's a project where you used LangChain hands-on?
- Walk me through how you've used Azure OpenAI in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: AI Evaluation, NLP, OpenAI, LangChain, and Azure OpenAI. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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