Data Analyst Sr

Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values -driven culture, international careers and the chance to shape the future of experience.

The opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries.

We are proud of:

• The work we do and the innovation we drive

• Our values of share, care a nd dare

• Our borderless, global framework, which enables seamless collaboration

The role

As a  Data Analyst , you are passionate about experience innovation and eager to push the boundaries of what’s possible. You bring 3+ YEARS  of experience, a growth mindset and a drive to make a lasting impact.

The Sr Data Analyst is a mid-level practitioner role within Analytics, Intelligence, & Optimization. This role is responsible for leading substantial portions of reporting, dashboarding, and performance analysis workstreams that help teams understand business performance, identify opportunities, and support decision-making. The Sr Data Analyst works independently across recurring and ad hoc analytics needs, translates business questions into analytical approaches, and delivers clear, actionable insights to internal and client stakeholders. At this level, the role is expected to demonstrate strong analytical judgment, reliable execution, and growing leadership in how reporting logic, metric consistency, and insight generation are applied across engagements.

You will thrive in this role if you are:

• A curious problem solver who challenges the status quo

• A collaborator who values teamwork and knowledge-sharing

• Excited by the intersection of technology, creativity and data

• Experienced in Agile methodologies and consulting (a plus)

Role responsibilities

• Lead the development, enhancement, and ongoing management of dashboards, reporting solutions, and recurring performance analysis.

• Translate business questions into structured analytical approaches, reporting requirements, data needs, and output designs with limited oversight.

• Analyze structured data to identify trends, anomalies, business drivers, and actionable opportunities.

• Own lightweight transformation logic and dashboard-ready data modeling needed to support accurate and scalable analytics outputs.

• Apply and reinforce semantic modeling practices by defining, documenting, and maintaining consistent business logic for metrics, dimensions, and KPIs.

• Validate data quality, troubleshoot reporting issues, and resolve moderately complex data logic challenges in partnership with adjacent teams where needed.

• Synthesize analysis into clear findings, implications, and recommendations for internal and client stakeholders.

• Support stakeholder discussions by clearly explaining performance changes, report logic, assumptions, and recommended actions.

• Partner with Measurement Implementation Analysts, CRO Analysts, SEO / GEO Specialists, Analytics Engineers, and DEPA teams to ensure analytics outputs align to measurement design, platform realities, and business needs.

• Improve analytics delivery by identifying opportunities for better reporting structure, cleaner metric definitions, improved documentation, and more scalable analysis workflows

• Contribute to governance discipline by following established privacy, measurement, and data-quality standards in day-to-day work.

Must have qualifications

To be considered for this role, you must meet the following essential qualifications:

• Strong working knowledge of digital analytics, reporting, dashboarding, and performance measurement.

• Ability to independently manage recurring analytics workstreams and produce reliable outputs with minimal oversight.

• Strong understanding of data structures, joins, dimensions, metrics, KPI logic, and dashboard design principles.

• Ability to turn data into clear, business-relevant insights and recommendations.

• Strong analytical problem-solving skills, including the ability to investigate anomalies and identify likely drivers of performance.

• Working knowledge of semantic modeling and the role of consistent business definitions in scalable analytics.

• Ability to balance technical accuracy with stakeholder usability in reports and dashboards.

• Strong written and verbal communication skills in English, including the ability to present findings clearly to non-technical audiences.

• Strong attention to detail with a disciplined approach to validation, QA, and documentation.

• Ability to work effectively across distributed teams in the Americas and collaborate across functions, time zones, and client contexts.

AI Fluency / AI-Assisted Analytics Expectations

Expected to be an active adopter of approved AI-enabled analytics and productivity tools that improve the speed, clarity, and quality of reporting, insight generation, documentation, and stakeholder communication. Uses AI-assisted workflows to help explore patterns, summarize findings, draft analysis narratives, validate assumptions, improve metric documentation, and accelerate repeatable reporting tasks while maintaining human accountability for analytical judgment, data accuracy, business interpretation, and final recommendations.

Understands that AI-generated analysis, summaries, or recommendations must be checked against source data, metric definitions, business context, and governance expectations before being shared or used for decision-making. Demonstrates curiosity and practical enthusiasm for how AI can improve analytics quality, productivity, and decision support without replacing disciplined analysis or stakeholder reasoning.

At this level, AI fluency means reliable use within workstreams. Expected to apply approved AI-assisted workflows to improve delivery quality, repeatability, documentation, and stakeholder communication, and to help junior practitioners understand where AI can and cannot be used responsibly.

Tools / Platforms

Analytics & Reporting

• Google Analytics 4 (GA4)

• Adobe Analytics

• Other digital analytics platforms as needed

Visualization & BI

• Looker

• Power BI

• Tableau

• Looker Studio

Data & Querying

• SQL

• BigQuery

• Snowflake

• Excel

• Google Sheets

Optimization / Experience / CDP Ecosystem

• Optimizely

• Adobe Target

• Dynamic Yield

• CDP and optimization tools as relevant to the client environment

Nice to have qualifications

• Google Analytics certification or equivalent GA4 learning path

• Adobe Analytics learning path or platform training

• Looker, Tableau, or Power BI certification

• SQL certification or equivalent applied coursework

• Additional analytics, BI, or experimentation platform training as relevant

Collaboration / Stakeholder Expectations

• Serves as a dependable analytics partner to internal teams and client stakeholders across reporting, dashboarding, and insight generation needs.

• Collaborates closely with Measurement Implementation Analysts to ensure reporting reflects tracking strategy, event design, and instrumentation logic.

• Works with CRO Analysts and SEO / GEO Specialists to integrate experimentation, conversion, and organic performance insights into broader business analysis where relevant.

• Partners with Analytics Engineers and DEPA teams when reporting requirements, data logic, or semantic definitions require more scalable or technical solutions.

• Participates confidently in client-facing discussions by explaining methodology, findings, reporting logic, and implications in clear business language.

• Helps create consistency across team delivery by improving documentation, sharing best practices, and supporting more junior practitioners.

People Ma