Insights Factory-Data & Analytics Engineer-Senior Associate

Overview

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems.

You will play a crucial role in organizing & maintaining proprietary datasets and transforming data into insights & visualizations that drive strategic decisions for our clients and the firm. You’ll work closely with the industry leader & a number of cross-functional retail & consumer advisory, tax and assurance professional teams to develop high-impact, commercially relevant insights to infuse into thought leadership, external media engagement, demand generation, client pursuits, & delivery enablement.

Knowledge And Skills Preferred

Demonstrates in- depth level abilities and/or a proven record of success managing efforts with identifying and addressing client needs:

• As a critical member of a team of the data science team, you will maintain and analyze large, complex datasets to uncover insights that inform topics across the Financial Services sector.
• Support in the identification of new, cutting-edge datasets that add to the firm's differentiation amongst competitors and clients;
• Support in building predictive models and data-led tools;
• Design and conduct experiments (A/B testing, market basket analysis, etc.) to measure the effectiveness of new approaches and drive continuous improvement;
• Partner with US team to translate analytical findings into actionable recommendations and compelling stories;
• Develop dashboards and reports using tools like Tableau, Power BI, or Looker to support self-service analytics and decision-making;
• Stay up to date and ahead of industry trends, customer behavior patterns, and emerging technologies in the aligned sector.
• Experience managing high performing data science and commercial analytics teams;
• Strong SQL and Alteryx skills and proficiency in Python and/or R for data manipulation and modeling;
• Experience applying machine learning or statistical techniques to real-world business problems;
• Solid understanding of key Industry specific metrics
• Proven ability to explain complex data concepts to non-technical stakeholders;
• Experience with Industry specific datasets and vendors
• Knowledge of geospatial or time-series analysis and,
• Prior work with commercial analytics and insights
  
  

• 4-8+ years in analytics engineering, data consulting, BI/analytics delivery, or adjacent roles with end-to-end ownership.
• Strong SQL and data modeling fundamentals (dimensional modeling, metric design, data cleanliness principles).
• Python for analysis and automation (pandas, APIs, scripting, workflow automation).
• Proven ability to communicate with senior stakeholders: strong interpersonal communication, structured thinking, clear documentation.
• A track record of translating ambiguity into shipped outcomes (not just executing tasks).
  
  

• Experience with Databricks (Spark basics, notebooks/jobs, Delta patterns) and/or Azure (storage, access patterns, data services).
• Familiarity with modern ELT tools and practices (dbt, orchestration, CI/CD for data, monitoring).
• Financial Services domain experience (banking, insurance, capital markets, risk/compliance).
• Power BI skills (semantic modeling, DAX, Power Query)—useful but not the center of the role.
  
  

We are specifically looking for navigators, not passengers. In this role, high performance looks like:

• You bring clarity when requirements are fuzzy (and you document decisions).
• You spot blockers early and propose mitigation, rather than waiting for direction.
• You communicate proactively—status, risks, scope changes—with no surprises.
• You take ownership of the “last mile”: the insight is clear, the output is usable, and the stakeholder knows what to do next.
• You care about impact and value more than activity—and you push toward the highest leverage work.