Senior Data Analytics Engineer (5+ years only with Python, Power BI, SQL)

Posted 3 Days Ago
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Pune, Maharashtra, IND
In-Office
Senior level
Information Technology • Software
The Role
Lead analytics initiatives by architecting enterprise Power BI dashboards, automating reporting with Python and Fabric, building and deploying ML/GenAI models, mentoring junior analysts, collaborating with finance for advanced analytics, and driving data governance and adoption across cross-functional teams.
Summary Generated by Built In

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.

Skills Required

  • Bachelor's degree in data science, analytics, computer science, engineering, or related quantitative field
  • 5+ years hands-on experience in data analysis, business intelligence, or analytics roles
  • Proven experience leading analytical initiatives, building and deploying AI/ML models, and delivering enterprise-grade dashboards
  • Demonstrated experience mentoring junior analysts and guiding cross-functional data projects
  • Strong proficiency in Python for data manipulation and automation (Pandas, NumPy, SciPy, Statsmodels, Matplotlib, Seaborn, Plotly)
  • Expert-level Power BI skills including DAX, Power Query, and data modeling (Tableau experience acceptable)
  • Advanced SQL skills, data modeling, schema design, performance tuning, and data quality principles
  • Extensive experience building, validating, and deploying predictive, classification, and clustering models (Scikit-learn, XGBoost, TensorFlow, PyTorch)
  • Experience with GenAI tools and frameworks (e.g., LangChain, OpenAI APIs, Azure OpenAI) for automation and NLP
  • Familiarity with Microsoft Fabric and integration within modern data ecosystems, Azure Data Factory, or similar cloud platforms
  • Knowledge of Git, CI/CD pipelines, and DevOps practices for reproducible, scalable analytics workflows
  • Experience with PySpark for large-scale data processing
  • Master's degree in related field
  • Background in finance domain
  • Strong written and verbal communication, stakeholder management, and ability to present technical concepts to non-technical audiences

Wolters Kluwer Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Wolters Kluwer and has not been reviewed or approved by Wolters Kluwer.

  • Leave & Time Off Breadth Time away benefits are positioned as broad, spanning vacation and sick time plus paid holidays and other covered leave types. Paid parental and caregiver leave, bereavement leave, and a volunteer day contribute to a more comprehensive time-off offering.
  • Retirement Support Retirement support is framed as meaningful through access to a 401(k)/retirement plan paired with company matching and additional contribution features in some descriptions. This is reinforced by mentions of profit sharing and other long-term savings-oriented programs.
  • Parental & Family Support Family-oriented support stands out through adoption assistance and paid parental leave provisions. These benefits are described alongside other caregiver supports that extend beyond basic leave categories.

Wolters Kluwer Insights

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The Company
HQ: Alphen aan den Rijn
18,996 Employees

What We Do

Wolters Kluwer (www.wolterskluwer.com) is a global leader in information services and solutions for professionals in the health, tax and accounting, risk and compliance, finance and legal sectors. We help our customers make critical decisions every day by providing expert solutions that combine deep domain knowledge with specialized technology and services. Founded in 1836 and headquartered in Alphen aan den Rijn, the Netherlands, the company serves customers in over 180 countries, maintains operations in over 40 countries and employs 18,600 people worldwide. Wolters Kluwer reported 2019 annual revenues of €4.6 billion. Listed on Euronext Amsterdam, Wolters Kluwer shares (WKL) are included in the AEX and Euronext 100 indices. Wolters Kluwer has a sponsored Level 1 American Depositary Receipt program. The ADRs are traded on the over-the-counter market in the U.S. (WTKWY).

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