Adorama Ukraine

We are looking for a data-driven Marketing Analyst to support performance tracking, reporting, and insights across our digital marketing channels.

This role is focused on analyzing marketing performance, building dashboards, and translating data into actionable insights that inform decision-making across the business.

The ideal candidate has hands-on experience with tools like GA4 and Looker (or similar BI tools), understands how digital marketing channels contribute to ecommerce performance, and is comfortable turning analysis into clear PowerPoint presentations for stakeholders.

This is not a campaign execution role — the focus is on measurement, analysis, reporting, and business visibility into performance.

Key Responsibilities

Performance Reporting & Analysis

• Pull, analyze, and interpret data across digital channels, including paid media, email, organic, and direct

• Build and maintain recurring reports on key KPIs such as traffic, conversion, revenue, CAC, and other performance metrics

• Identify trends, anomalies, and opportunities to improve performance

• Support campaign recaps, business reviews, and ad hoc analysis

Dashboarding & Data Visualization

• Build and maintain dashboards in Looker or similar BI tools

• Ensure stakeholders have clear, consistent visibility into performance

• Improve reporting efficiency and help standardize key metrics across teams 

Analytics & Tracking

• Work with GA4 to analyze user behavior, traffic sources, and conversion paths

• Help ensure data accuracy and consistency across reporting platforms

• Support UTM tracking and campaign measurement frameworks

Presentation Development

• Build clear, polished PowerPoint presentations to communicate marketing performance, trends, and insights

• Translate data into executive-friendly visuals and narratives for internal stakeholders

Project Support & Coordination

• Assist with light Jira ticket management and task tracking

• Keep team members updated and aligned through clear, timely communication

Cross-Functional Support

• Partner with channel owners across paid, email, SEO, and related functions to provide insights and reporting

• Support leadership with data-driven recommendations

• Assist in translating business questions into structured analysis

Qualifications

• 2–4 years of experience in marketing analytics, digital analytics, or a similar role

• Hands-on experience with GA4 and Looker or comparable BI tools such as Tableau or Power BI

• Strong analytical skills and ability to interpret data and communicate insights clearly

• Solid understanding of B2C digital marketing and ecommerce metrics

• Strong Excel / Google Sheets skills

• Comfortable creating stakeholder-ready PowerPoint presentations

Preferred Skills

• Experience working with large datasets; BigQuery or similar is a plus

• Understanding of attribution models and channel performance measurement

• Experience building dashboards for business stakeholders

• Familiarity with Jira or similar project management tools

• Familiarity with CRM or customer data is a plus

Role Summary

The Inventory & Demand Planning team is hiring a Data Analyst to scale a high-impact analytics roadmap across inventory, in-stock, supply, and forecasting. This role builds and maintains the data foundation that powers decision-making by translating business rules into reliable datasets, automating recurring KPI outputs, and supporting the ABC/XYZ + lifecycle governance framework so leaders and merchants operate from consistent, auditable numbers with minimal manual effort.

This is a hands-on analytics engineering role centered on data pipelines, automation, and metric integrity to enable planning decisions and streamline reporting/governance outputs. The analyst will partner closely with Inventory Planning leadership to implement definitions, validations, and scalable reporting.

What You’ll Work On

· Build and maintain curated BigQuery tables/views that standardize inventory, demand, availability, open POs/in-transit, backorders, and KPI feeds.

· Write clean, performant SQL that powers weekly/monthly reporting and executive dashboards.

· Automate refreshes and reduce manual effort through validations, reconciliations, exception flags, and clear documentation.

· Support ABC/XYZ roadmap execution by producing required inputs/outputs, applying multiplier logic, and keeping the classification pipeline stable and easy to audit.

· Support forecasting improvements using Python (data prep, feature engineering, back-testing, evaluation) and help operationalize outputs into cadence reporting.

· Expand datasets with additional signals where available (promo flags/types, merchandising tags, launch/NPA indicators, traffic/CVR signals, marketing calendar attributes).

· Partner with Merchandising, Marketing Ops, Finance, and BI/IT to align definitions, improve data quality, and drive adoption of standardized metrics.

How Success Will Be Measured

· KPI tables and dashboard feeds refresh reliably with minimal manual intervention.

· Faster turnaround on leadership and merchant requests with consistent, traceable metric logic.

· ABC/XYZ outputs are accurate, on-time, and easy to maintain.

· Forecast inputs improve through better data structure and added business/marketing signals.

· Documentation and change control keep datasets stable as business rules evolve.

Required Qualifications

· 3–5 years in analytics/data roles (retail/e-commerce strongly preferred).

· Strong SQL and hands-on experience with BigQuery (or similar cloud warehouse).

· Working Python proficiency for analysis/automation (pandas/NumPy).

· Experience supporting BI dashboards and recurring reporting.

· Demonstrated ability to validate and reconcile metrics across sources, troubleshoot discrepancies, and document logic clearly.

· Strong problem-solving, attention to detail, and clear communication with business stakeholders.

Preferred Qualifications

· Familiarity with ML/forecasting workflows (feature engineering, evaluation, operationalizing outputs) to support forecasting and driver-based models in partnership with the team.

· Familiarity with Looker/LookML (or similar semantic layers).

· Exposure to dbt and/or orchestration tools (Airflow/Composer or equivalents).

· Comfort with inventory/planning concepts (WOS, aging, availability, lost demand, backorders) and classification/ranking approaches (ABC/XYZ, PFEP).

· Version control (Git) and basic engineering hygiene (testing, documentation, change logs).

Tools / Environment

BigQuery, SQL, Python, Looker, Jira/Confluence (or equivalent), Google Cloud tooling as applicable.