Data Analyst- Consultant Full Time

GreedyGame works at the intersection of mobile advertising, app monetization, user acquisition, and publisher growth. We are looking for a Data Analyst / Data Engineer who can work with large-scale ad-tech and monetization data and turn it into clear, actionable insights.

In this role, you will help us process and analyse high-volume data across ad requests, impressions, clicks, installs, revenue, user behaviour, and partner performance. Your work will directly impact how we improve publisher revenue, optimise ad performance, monitor platform efficiency, and make sharper product and business decisions.

You will work closely with Engineering, Product, AdOps, Business, and Monetization teams to build reliable data pipelines, create meaningful dashboards, and identify opportunities for revenue and performance improvement.

This is a hands-on role for someone who enjoys working with messy, high-scale data and can connect the dots between data systems, product behaviour, and revenue outcomes.

Key Responsibilities Data Pipelines & Infrastructure

• Build and maintain scalable data pipelines to process large volumes of ad-tech events such as ad requests, impressions, clicks, installs, conversions, and revenue signals.
• Create ETL workflows for data coming from ad networks, SDK events, internal services, publisher platforms, and monetization partners.
• Optimise data warehouse schemas, data models, and queries for faster reporting and analytics.
• Monitor data quality, accuracy, latency, and reliability across pipelines.
• Identify gaps in tracking, reporting, and event instrumentation, and work with engineering teams to fix them.

Monetization & Product Analytics

• Analyse key advertising and monetization metrics such as:
• eCPM
• Fill Rate
• Match Rate
• ARPDAU
• Impressions
• Ad Requests
• CTR
• Revenue per user
• Publisher revenue trends
• Generate insights to improve ad yield, publisher monetization, and platform performance.
• Work with product teams to analyse ad placement performance, user engagement, retention, and revenue impact.
• Identify patterns across apps, publishers, geographies, ad formats, and demand sources.
• Help business and AdOps teams understand what is driving revenue movement — and what needs immediate attention.

Experimentation & Optimization

• Support A/B tests around ad placements, formats, floors, user flows, offerwall placements, and monetization strategies.
• Build frameworks to measure experiment impact, revenue lift, user impact, and long-term performance.
• Identify opportunities to improve auction efficiency, ad delivery, fill rate, and user experience.
• Partner with product and monetization teams to convert data observations into practical experiments.

Dashboards, Reporting & Data Accessibility

• Build dashboards and reporting systems used by Product, AdOps, Business, Leadership, and Publisher Success teams.
• Define and maintain key business and product metrics across GreedyGame’s monetization platforms.
• Create automated reports that reduce manual analysis and improve visibility across teams.
• Translate complex data into simple insights that help teams take faster decisions.
• Improve the overall data accessibility and reliability for internal stakeholders.

Required Skills

• Strong hands-on experience with SQL and data querying.
• Programming experience in Python / Scala.
• Experience building ETL pipelines and data workflows.
• Experience with data warehouses such as BigQuery, Snowflake, Redshift, or similar platforms.
• Understanding of large-scale event data processing.
• Experience with dashboarding tools such as Looker, Tableau, Metabase, Superset, or similar tools.
• Strong analytical thinking and ability to connect data with business outcomes.
• Ability to work with cross-functional teams and convert open-ended business questions into structured analysis.
• Comfort with debugging data inconsistencies, tracking gaps, and reporting mismatches.

Good to Have

• Experience in AdTech, programmatic advertising, mobile monetization, or gaming analytics.
• Familiarity with platforms such as GAM, AdMob, ironSource, Unity Ads, AppLovin, Meta, or similar ad platforms.
• Experience with high-throughput streaming systems such as Kafka, Spark, or Flink.
• Understanding of RTB, ad auctions, ad mediation, waterfalls, bidding, and yield optimization.
• Exposure to mobile app analytics, gaming monetization, offerwall, or rewarded advertising.
• Experience working with revenue, publisher, or advertiser-side analytics.

What Makes This Role Interesting

• You will work on high-scale advertising and monetization data across mobile apps, publishers, and demand partners.
• Your insights will directly influence publisher revenue, ad yield, product decisions, and monetization strategy.
• You will solve real problems around data accuracy, revenue movement, experiment impact, and platform performance.
• You will work closely with teams that own product, engineering, AdOps, and business outcomes — not just reporting.
• You will get exposure to the core mechanics of ad monetization, user acquisition, offerwall, and publisher growth.

Ideal Candidate

We are looking for someone who is not just good at writing queries, but can ask the right questions.

Someone who can look at a revenue dip and figure out whether it is a tracking issue, fill-rate issue, demand-side issue, product change, geo impact, or publisher-level pattern.

Someone who enjoys working in a fast-moving startup environment where data is not only used for reporting, but for making real product and business decisions.

Skills: revenue,reporting,python,data