Data Platform Manager

Data Platform Manager - Europe

i-Genie.ai

Consumer Insights AI - Augmented Intelligence - driving superior marketing outcomes

Data Platform Manager - Europe

• 80k – 100k
• Remote (Europe)
• 10 years of exp
• Full Time

Posted: today Recruiter recently active

Hires remotely in Europe

Remote Work Policy Remote only

Company Location Europe New York City United States United Kingdom

Visa Sponsorship Not Available

RelocationAllowed

Skills

• Python
• SQL
• Tableau
• Pandas
• Sprinklr
• Brandwatch
• Looker
• Microsoft Power BI
• Talkwalker
• Youscan
• Hiring contact
• Supreeth Balasubramanya
• Employee
• Georgia

About the job

About the role

Location - Europe

i-Genie.ai is transforming how the world’s leading consumer brands - including Unilever, Kenvue, Bayer, and Coca-Cola - discover, understand, and act on consumer insights. Our AI-driven platform, which includes Brand Pulse, ImpactIQ, Trend Spotter, Innov8 and customer facing AI assistant Presto, delivers real-time brand health tracking, trend detection, and product benchmarking, helping teams turn complex data into clear actions.

Our platform ingests and reconciles high-volume, high-variance data from search, LLM visibility, social listening, e-commerce sources turns it into decision-ready insight for brand and marketing teams.

We're expanding the data foundation of the platform: recently added LLM visibility (brand presence and sentiment across AI answer engines), with e-commerce and social visibility data sources to follow. At the same time, we're tightening the reliability of our existing pipelines - cross-market, cross-platform data reconciliation, classification accuracy, and dashboard data delivery are our highest priority as we scale into more markets and categories.

We're hiring a Data Product Manager to own the data layer of our product suite: defining what data we ingest, how it's modeled and validated, how discrepancies get triaged, and how new data sources get integrated cleanly into the platform.

What you'll do

• Own strategy, commercials, SLAs, and escalations for all data vendors. Scout, evaluate, select, and brief new sources, and hand each to Data Engineering integration-ready, staying on point for vendor-side issues until live.

• Own the product roadmap for the platform's data layer across search, social, review, llm and eCom data sets, as well prioritizing data quality, coverage, and new source integration alongside feature delivery.

• Lead the integration of new data sources into the platform, such as LLM visibility (brand presence/sentiment in AI answer engines), e-commerce and expanded social visibility data or first-party customer care data.

• Ensure data has optimal reuse and utility across our platform of applications - ImpactIQ, TrendSpotter, Innov8, Brand Pulse - and our agentic layer Presto.

• Own the measurement and reporting of quality of the end-to-end data processing pipeline including source selection, data ingestion, data processing, metadata enhancement and interpretation, ensuring quality control and measures at each step. Use the metrics to prioritize where we spend engineering resource

• Define data quality standards and own resolution of discrepancies between production and test data (e.g. cross-platform reclassification drift, duplicate/collision handling, lookback-window and refresh-cadence issues) in partnership with data science and data engineering.

• Translate messy, multi-platform social/e-commerce data (metric definitions, taxonomy differences, owned vs. non-owned channel distinctions) into clear, client-facing data models and documentation.

• Work directly with data quality/QA analysts to prioritize and unblock investigations into metric discrepancies across markets and categories.

• Build and maintain internal documentation of platform data capabilities (metric availability by source, coverage by market/category) to support both product decisions and client-facing conversations.

• Define requirements and success metrics for new features, working closely with product, design, engineering, and client-facing teams.

• Represent the voice of the data in client-facing conversations - explaining known data behaviors, limitations, and roadmap to clients and internal stakeholders.

• What we're looking for

• 5-7 years of experience in data product management, with a significant portion focused on data products, analytics platforms, or data-intensive SaaS.

• Strong working knowledge of BI/visualization tools (Power BI, Tableau, Looker, or similar) - able to critically review dashboards, not just request them. Experience working with large, messy, multi-source datasets: deduplication, reconciliation, classification/taxonomy work, or similar data quality challenges.

• Comfort with SQL and enough data fluency (Python/pandas a plus) to independently investigate discrepancies and validate engineering output. To interrogate the outputs and dashboards brought to you.

• Experience defining data models, schemas, or taxonomies for a product, ideally in a domain with subjective/unstructured inputs (social, text, sentiment, or similar).

• Familiarity with LLM-powered product features (prompting, LLM-based classification or summarization) is a plus given our platform's direction.

• Excellent written and verbal communication - able to explain data nuance to both engineers and non-technical CPG/marketing stakeholders.

• Comfortable operating across multiple products and priorities in a fast-moving environment.

• Experience with social listening or review-monitoring platforms (Brandwatch, YouScan, Sprinklr, Talkwalker, or similar) as a user or product owner.

• 2+ years managing external data vendors: SLAs, quality audits, source evaluation, commercials.

• Nice to have

• Hands-on experience with Databricks (or an equivalent modern data platform) - comfortable enough to work directly with data engineers on pipeline design, schema decisions, and data validation, not just consume dashboards.

• Experience evaluating or integrating third-party vendor data/APIs into an existing platform.

• Background in CPG, FMCG, or brand marketing analytics.

What We Offer

Global remote work: No physical office, work from anywhere

Ownership & impact: Shape architecture decisions for a fast-growing platform

Competitive compensation: Creative short and long-term packages designed to create wealth as we grow

Cutting-edge problems: Real-world challenges at scale with the latest ML/NLP technologies

Autonomy: We trust you to deliver exceptional work on your terms

About the company

i-Genie.ai

Consumer Insights AI - Augmented Intelligence - driving superior marketing outcomes Europe

51-200

Marketing Services

SaaS

Artificial Intelligence

Enterprise Software Company

Big Data Analytics

Analytics

Big Data

Artificial Intelligence

Brand Marketing

Predictive Analytics

Big Data Analytics

B2B · SaaS · Mobile · Artificial Intelligence / Machine Learning

Learn more about i-Genie.ai

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