[Remote] Data Analytics Engineer

Note: The job is a remote job and is open to candidates in USA. Harrison Clarke is recruiting for a fast-growing SaaS platform in the creator/media space. The Data Analytics Engineer will build the Ad Network’s data foundation, including data models, standardized KPIs, and reporting, while owning dashboards, analyses, and data quality improvements.

Responsibilities

• Design and build the data model for the ad network - fact tables, aggregation tables, and the transformation layer behind reporting and analysis
• Standardize KPIs and business metrics (CPC, CPA, CPM and beyond) into a trusted single source of truth
• Build and own BI dashboards, and run deep-dive, ad-hoc analyses to surface patterns and opportunities
• Monitor data flows for anomalies and quality issues, and improve tracking and instrumentation with the engineering team

Skills

• ~3+ years as a Data Analyst, Analytics Engineer, or similar at a SaaS or high-growth tech company
• Excellent SQL
• Genuine data modeling on an OLAP / columnar database (ClickHouse, Redshift, BigQuery, Snowflake) — you understand how these databases actually work: partitioning, aggregation design, query performance
• Strong dbt (or equivalent) experience — designing your own staging/intermediate/mart models and a clean semantic layer
• Hands-on BI/dashboarding (Metabase, Looker, Tableau, Sigma, Mode, or similar — tool skills transfer)
• A clear communicator who turns complex data into a clear narrative for technical and non-technical audiences
• US-based only
• Some statistical/analytical modeling (the kind of analysis that, at some companies, sits under a data-science title)
• Python for analysis
• Ad tech / ad network / marketing-analytics background (CPM/CPC/attribution)
• Entity resolution / identity-stitching experience (a later initiative on the roadmap)

Benefits

• Equity
• Fully remote; US-based only

Company Overview