Posted 17 days ago
Data Product Analyst
@ EXL Talent Acquisition Team
Canada
Overview
EXL Talent Acquisition Team is hiring a Data Product Analyst to bridge business stakeholders and data engineering for its international data platform. The role owns the path from business request to trusted production data, including requirements, delivery follow-through, and ongoing data quality monitoring. The posting requires 5+ years of analysis experience with extensive SQL and Python skills.
Responsibilities:
- Elicit and document business and functional requirements
- Query and validate data to investigate anomalies and uncover insights
- Own delivery after handoff to data engineering
- Monitor data quality and build business-rule alerts
- Define acceptance and UAT criteria
Requirements summary:
- Bachelor's degree or equivalent experience
- 5+ years in data analysis or analytics roles
- Advanced SQL with Python proficiency
- Cloud data platform and ETL/ELT knowledge
- Strong communication and cross-functional collaboration
Tools & skills
Source and dates
Employer career site / ATS feed · oraclecloud
- Employer posting date
- 2026-10-20
- First seen by our source
- 2026-10-20
- Source record updated
- 2026-10-20
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Mid level |
| Department | Data & analytics |
| Experience | 5+ years |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
| Education | Bachelor’s degree (required) |
| Fields of study | Information systems, Computer science, Data analytics |
Summary and details written by AI from the posting; the employer’s posting is the authority.
EXL Talent Acquisition Team
Saved company profile
Historical company information from a saved The Jobs API profile (LinkedIn/Crunchbase fields). It is not live-verified; figures may have changed. Missing values remain unknown.
Full company description
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.
- LinkedIn followers
- 2,037,193
- People associated on LinkedIn
- 51,202
- Reported office locations
- 320 Park Avenue, 29th Floor, New York, NY 10022, US
- 10 Exchange Pl, Jersey City, NJ 07302, US
- Business categories
- Information Technology
- Health Care
- Banking
- Consulting
- Management Consulting
- Analytics
- Outsourcing
- Other recorded names
- EXL Service
- EXL
- EXL Talent Acquisition Team
- Specialties
- Operations Management
- Decision Analytics
- Technology Platforms
- Healthcare
- Finance & Accounting
- Insurance
- Risk & Financial Management
- Travel
- Transportation and logistics
- Banking and Financial Services
- Operations & Process Excellence
- Utilities
- Analytics
- Digital Transformation
- Management Consulting
- Finance Transformation
- IT Audit
- Artificial Intelligence
- Automation
- Robotics
- Machine Learning
- and NLP
- Profile identifies a recruitment agency
- No
- Reported total investment
- 1,150,000,000
Currency and observation date were not supplied; this is not a current valuation or a funding round.
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…
| Field | Value |
|---|---|
| Industry | Business Consulting and Services |
| Company size | 10,001+ employees |
| Headquarters | New York, NY |
| Organization type | Public Company |
| Specialties | Operations ManagementDecision AnalyticsTechnology PlatformsHealthcareFinance & AccountingInsuranceRisk & Financial ManagementTravelTransportation and logisticsBanking and Financial Services |
| Open jobs on Jobsy | 12 |
| View page |
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.
Act 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.
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