The ideal candidate combines deep technical expertise in analytics engineering with strong product analytics acumen and stakeholder management skills. You will work closely with client Product Managers, Data Engineers, Data Scientists, and business leaders to design, develop, and operationalize modern analytics solutions that improve product measurement, experimentation, and business outcomes.
As an EXL consultant, you will play a critical role in translating business objectives into scalable data products, ensuring analytical rigor, data quality, and operational excellence across the analytics ecosystem.
Analytics Engineering & Data Product Development
- Design, build, and maintain scalable analytics engineering solutions leveraging Databricks, Unity Catalog, and modern data platform capabilities.
- Develop and manage metrics-as-code frameworks, enabling standardized, governed, and reusable business metrics across product domains.
- Implement metric, cohort, segment, and KPI definitions within enterprise semantic layers and measurement platforms.
- Build and optimize Workstream Scorecards that connect strategic objectives, business drivers, performance indicators, and actionable insights.
- Develop automated data pipelines supporting metric refreshes, data validation, and reporting workflows.
- Create scalable analytics assets, reusable frameworks, and data products that accelerate business adoption and decision making.
- Establish best practices for data modeling, metric governance, version control, testing, and deployment. Partner with Data Engineering teams to define source data requirements, event tracking standards, and instrumentation strategies.
- Lead efforts to improve data quality, observability, lineage, and governance across analytics environments.
Product Analytics & Experimentation
- Partner with client stakeholders to translate business questions into measurable product KPIs and actionable insights.
- Develop product measurement frameworks focused on engagement, retention, acquisition, conversion, and customer lifecycle performance.
- Support experimentation initiatives through metric definition, experiment design consultation, and outcome measurement.
- Build and maintain customer cohorts, segmentation frameworks, and behavioral analysis models.
Engineering Excellence & Delivery Leadership
- Champion software engineering best practices within analytics development, including CI/CD, code reviews, testing, and release management.
- Manage Git-based development workflows and deployment pipelines.
- Document metric definitions, business logic, transformation rules, and data quality considerations.
Required Qualifications
- 4+ years of experience in Analytics Engineering, Product Analytics, Data Analytics, or Business Intelligence.
- Advanced SQL expertise with demonstrated experience analyzing large-scale event, clickstream, behavioral, or customer interaction data.
- Strong hands-on experience with Databricks, Unity Catalog, Delta Lake, and modern cloud data platforms.
- Experience with metrics-as-code and semantic layer technologies such as dbt, Cube, MetricFlow, or similar frameworks.
- Proficiency in Python for analytics, data processing, automation, and testing.
- Experience working with Git, CI/CD pipelines, code repositories, and software development lifecycle practices.
- Deep understanding of product analytics concepts including funnels, cohorts, DAU/WAU/MAU, retention, engagement, conversion, and customer journey analysis.
- Strong experience partnering with product, engineering, and business stakeholders to deliver analytical solutions.
- Excellent communication, consulting, and stakeholder management skills.
- Experience working in agile delivery environments and distributed teams.
Preferred Qualifications
- Experience supporting product experimentation and A/B testing programs.
- Exposure to AI/LLM evaluation frameworks, prompt engineering, or analytics copilots.
- Experience in media, streaming, digital subscription, or consumer-facing products.
- Familiarity with Tableau, Power BI, Looker, or similar visualization platforms.
- Experience with event-tracking tools such as Adobe Analytics, GA4, Mixpanel, Amplitude, or similar platforms.
- Knowledge of cloud ecosystems including AWS, Azure, or GCP.
- Prior consulting or client-facing delivery experience preferred.
Skills Required
- 4+ years of experience in Analytics Engineering, Product Analytics, Data Analytics, or Business Intelligence.
- Advanced SQL expertise with experience analyzing large-scale event, clickstream, behavioral, or customer interaction data.
- Strong hands-on experience with Databricks, Unity Catalog, Delta Lake, and modern cloud data platforms.
- Experience with metrics-as-code and semantic layer technologies such as dbt, Cube, MetricFlow, or similar frameworks.
- Proficiency in Python for analytics, data processing, automation, and testing.
- Experience working with Git, CI/CD pipelines, code repositories, and software development lifecycle practices.
- Deep understanding of product analytics concepts including funnels, cohorts, DAU/WAU/MAU, retention, engagement, conversion, and customer journey analysis.
- Strong experience partnering with product, engineering, and business stakeholders to deliver analytical solutions.
- Excellent communication, consulting, and stakeholder management skills.
- Experience working in agile delivery environments and distributed teams.
- Experience supporting product experimentation and A/B testing programs.
- Exposure to AI/LLM evaluation frameworks, prompt engineering, or analytics copilots.
- Experience in media, streaming, digital subscription, or consumer-facing products.
- Familiarity with Tableau, Power BI, Looker, or similar visualization platforms.
- Experience with event-tracking tools such as Adobe Analytics, GA4, Mixpanel, Amplitude, or similar platforms.
- Knowledge of cloud ecosystems including AWS, Azure, or GCP.
- Prior consulting or client-facing delivery experience.
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.
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