Big Query/Data Studio Freelancer Application
Note: This is an ongoing live link. We will add your details to our talent pool and reach out if we have a project matching your skillset đź‘Ť
Pacing Agency is a London-based marketing team that helps businesses grow. We maintain a BigQuery data warehouse and use Data Studio (formerly Looker, formerly Data Studio 🙄) for client-facing reporting. We’re building a small roster of freelance specialists we can bring in when we need extra capacity, not a full-time seat, but repeat project work when dashboards, modeling, or handover need depth.
We're a small, hands-on team. We cut straight to the good stuff, using data and experience to get results. We need someone who works pragmatically in BigQuery and Data Studio: shape a reporting layer when raw data isn’t chart-ready (views or scheduled tables), keep queries cost-conscious, and deliver reports stakeholders can refresh and share confidently.
Near-term example: a lead report that lines up leads the client sends us (exports/CRM drops) with behaviour in BigQuery. Initially we’ll match primarily on form submission date and time; we’d eventually like tighter joins on a persistent user ID once that’s reliable end-to-end. For each reconciled lead, we want clarity on journey and paid touchpoints.
What You'll Be Doing
- Connecting BigQuery to Looker Studio using appropriate data sources (tables, views, or custom SQL) and sensible live vs extract choices.
- Designing and building dashboards with filters, clear KPIs, and layouts suitable for client sharing.
- Owning (or co-owning) the lead report model: joining client-supplied leads to session/click streams.
- Surfacing attribution-style metrics requested by stakeholders, e.g. first-touch and last-touch platform, counts of clicks tied to Google (gclid), Bing, and LinkedIn ads where those identifiers exist in our warehouse, plus session count and number of calendar days spanned by those sessions.
- Collaborating on data modeling where raw tables are nested or awkward for reporting.
- Working with our GCP access patterns (least-privilege roles, service accounts or OAuth - whatever we standardise on) so reports stay secure and maintainable.
- Documenting handover (field definitions, join logic, known gaps in click IDs), enough that we can extend the report without starting from scratch.
Must-Haves
- Strong hands-on BigQuery: comfortable exploring datasets and writing SQL (including views / scheduled queries when the reporting layer needs it).
- Proven Looker Studio delivery: you’ve shipped real reports from BigQuery, not only courses or experiments.
- Awareness of cost and performance: you think about bytes scanned, partitioning/clustering where relevant, and avoiding accidental full-table pulls in dashboards.
- Clear communication: you can explain trade-offs (raw vs modeled data, live vs extract) to a non-engineer stakeholder.
- Professional reliability: proactive, detail-oriented, and comfortable with client-facing polish.