The Data Product Analyst serves as a critical bridge between business stakeholders and data engineering for the international data platform. This role combines strong SQL and technical depth with core business analysis skills to ensure that data is trustworthy, accurately specified, and effectively leveraged to inform decision making. The Data Product Analyst owns the path from business request to trusted data in production: eliciting complete requirements, following the work through build and release, and monitoring the data once it is live. Over time, the role becomes the subject matter expert for international data.
ResponsibilitiesAct as the Data Subject Matter Expert to stakeholders, building deep knowledge of international data across the end‑to‑end data supply chain through hands-on work on every intake and production incident
Make international data trustworthy by working directly with business and marketing stakeholders to resolve data issues and build their confidence in the data.
Query, trace, and validate data from multiple sources to investigate anomalies, answer ad hoc requests, and uncover trends, patterns, and actionable insights.
Translate analytical findings into clear, business friendly insights that support decision‑making. Go beyond producing numbers: state what they mean in a sentence and anticipate the stakeholder's next question.
Elicit, document, and manage business, functional, and nonfunctional requirements through techniques such as interviews, workshops, process analysis, and user story creation. Write complete intakes that capture every requirement in as much detail as possible.
Own delivery after handoff: check in regularly with data engineering, confirm that what is built matches what was requested, and drive issues to resolution without waiting for direction.
Support prioritization by assessing business value, impacts, complexity, and risk.
Ensure traceability of requirements from intake through development, testing, and deployment.
Collaborate with data engineering analysts, architects, and engineers to ensure solutions reflect business context and use cases.
Define acceptance and UAT criteria that go beyond what the business specifies, including data accuracy, completeness, and edge cases; support user validation and provide structured feedback for continuous improvement.
Monitor and enhance data quality through profiling, validation, remediation, and alignment with organizational priorities.
Build and maintain business-rule monitors and alerts that catch business logic issues engineering's technical checks may miss, and review past incidents to close monitoring gaps.
Participate in PSG and release go/no-go meetings to stay informed on production changes that may affect data quality or reporting.
Manage time and availability: decide which meetings need active participation versus a recording and raise calendar overload or availability issues early.
Bachelor's degree in information systems, computer science, data analytics, or a related field, or equivalent experience.
5+ years of experience in data analysis, product analytics, analytics engineering, or similar roles, with extensive hands-on SQL experience.
Proven ability to work effectively in cross functional environments and support the delivery of data products that serve multiple stakeholders.
Demonstrated record of ownership: following requests through delivery and production and resolving issues across business and engineering teams.
Advanced SQL and analytical toolkit (with Python proficiency) used to explore, transform, and validate complex datasets across multiple product disciplines, including tracing data lineage and verifying data integrity without engineering dependencies.
Solid technical background in data modeling, ETL/ELT pipelines, and cloud data platforms (e.g., AWS), with enough depth to understand how data products are built and to partner credibly with engineers.
Skilled at requirements elicitation and translating business needs into technical specifications.
Skilled in crafting user stories, acceptance criteria, and high-quality product and data documentation to support scalable, repeatable workflows.
Strong understanding of data stewardship principles, including data quality, lineage, metadata management, and responsible data use and the ability to adapt analytical and stewardship skills across a wide range of use cases.
Comfortable connecting data across multiple systems and enriching datasets to enable new insights for business stakeholders.
Excellent communication, with the ability to tailor messages for both technical teams (engineering, data science) and business stakeholders.
Collaborative mindset with the ability to influence without authority and drive alignment across cross functional teams.
Thrives in ambiguity by asking clarifying questions, exploring new data sources, and uncovering insights that drive team action and improve data quality.
Strong critical thinking and structured problem-solving, especially when interpreting incomplete, messy, or evolving datasets.
Skills Required
- Bachelor's degree in information systems, computer science, data analytics, a related field, or equivalent experience
- 5+ years of experience in data analysis, product analytics, analytics engineering, or similar roles
- Extensive hands-on SQL experience
- Proficiency in Python for exploring, transforming, and validating complex datasets
- Experience working cross-functionally to deliver data products for multiple stakeholders
- Demonstrated ownership of requests through delivery, production, and issue resolution
- Knowledge of data modeling, ETL/ELT pipelines, and cloud data platforms such as AWS
- Ability to elicit requirements and translate business needs into technical specifications
- Ability to write user stories, acceptance criteria, and product and data documentation
- Understanding of data quality, lineage, metadata management, stewardship, and responsible data use
- Ability to connect data across multiple systems and enrich datasets
- Excellent communication with technical and business stakeholders
- Ability to influence without authority and drive cross-functional alignment
- Strong critical thinking and structured problem-solving skills
EXL Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about EXL and has not been reviewed or approved by EXL.
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Healthcare Strength — Medical plan options include HSA, HRA, and PPO choices, with additional health-related programs such as disability coverage and an employee assistance program. Feedback suggests these options provide meaningful flexibility and coverage breadth for many roles.
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Leave & Time Off Breadth — Up to 20 days of paid time off, plus federal holidays and paid sick and safe time, are highlighted. Feedback suggests this leave structure is a notable benefit alongside core compensation.
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Retirement Support — A traditional and Roth 401(k) with up to a 3% company match and full vesting after one year is described. Feedback suggests this match and vesting timeline help bolster long-term savings.
EXL Insights
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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