Senior Data Analyst
Full-timeJob Overview
We are looking for a talented and highly motivated Senior Data Analyst to join our Business Intelligence & Insights team and play a key role in shaping the data foundation that powers Kpler's commercial and strategic decision-making. Reporting to the Head of BI, you will own critical data pipelines, architect scalable Looker solutions, and act as a trusted data partner to stakeholders across the business.
This is a high-impact role for someone who thrives at the intersection of data engineering and business analytics, someone who can build robust, production-grade infrastructure one day and translate complex datasets into actionable insights for a commercial audience the next. If you're excited about working with real-time commodity flow data and helping shape the BI strategy of a fast-growing B2B SaaS company, this role is for you.
We are looking for a talented and highly motivated Senior Data Analyst to join our Business Intelligence & Insights team and play a key role in shaping the data foundation that powers Kpler's commercial and strategic decision-making. Reporting to the Head of BI, you will own critical data pipelines, architect scalable Looker solutions, and act as a trusted data partner to stakeholders across the business.
This is a high-impact role for someone who thrives at the intersection of data engineering and business analytics, someone who can build robust, production-grade infrastructure one day and translate complex datasets into actionable insights for a commercial audience the next. If you're excited about working with real-time commodity flow data and helping shape the BI strategy of a fast-growing B2B SaaS company, this role is for you.
Key Responsibilities
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Architect and maintain scalable LookML models, Explores, and dashboards that serve as the single source of truth for business metrics across commercial, product, and finance teams.
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Define and enforce best practices for Looker development including naming conventions, field definitions, derived tables, and data testing to ensure reliability and consistency.
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Own the end-to-end delivery of BI reporting features: from requirement gathering to data modelling to dashboard publication.
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Continuously optimise LookML for performance, leveraging BigQuery capabilities such as partitioning, clustering, and materialisation strategies.
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Is genuinely curious about AI tools and how they're evolving
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Proactively identifies opportunities to automate repetitive data tasks — whether that's query generation, documentation, or pipeline monitoring
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Uses AI to increase their own productivity and brings that mindset to the team
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Design, build, and maintain robust ELT pipelines in BigQuery that ingest, transform, and serve data from internal systems (CRM, ERP, product telemetry) and external APIs.
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Take ownership of pipeline reliability implement monitoring, alerting, and data quality checks to proactively identify and resolve issues before they reach stakeholders.
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Apply software engineering best practices to the BI codebase: version control via GitHub, peer code reviews, and thorough documentation.
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Identify technical debt and propose scalable, maintainable alternatives — always balancing speed of delivery with long-term data platform health.
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Partner directly with commercial, product, and finance stakeholders to translate ambiguous business questions into well-defined data requirements and analytical deliverables.
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Act as a trusted data advisor: proactively surface insights, flag data inconsistencies, and guide stakeholders in interpreting metrics correctly.
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Communicate complex technical concepts clearly and concisely to non-technical audiences, both in written documentation and live discussions.
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Contribute to data literacy across the organisation by promoting self-serve analytics and training stakeholders on Looker capabilities.
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Work closely with Data Engineering and Product teams to ensure BI needs are considered in upstream data architecture decisions.
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Contribute to team rituals — sprint planning, code reviews, design discussions — and help mentor junior team members.
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Support team OKRs and KPIs, and take accountability for the quality and accuracy of the analytical assets you own.
Looker & LookML Development
AI Curiosity & Experimentation
We're a team that actively explores how AI can make analytical work faster and sharper. For this role, we're looking for someone who:
Data Pipeline Ownership
Stakeholder-Facing Analytics
Cross-Functional Collaboration & Standards
Requirements
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5 years of experience in analytics, BI development, or a closely related data role.
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Solid understanding of data modelling principles: dimensional modelling, slowly changing dimensions, and denormalisation trade-offs.
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Experience working in a B2B SaaS environment, ideally with exposure to CRM data (Salesforce), product telemetry, or subscription billing datasets.
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Expert-level SQL skills with hands-on experience in BigQuery (or equivalent cloud data warehouse such as Snowflake or Redshift).
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Proven experience developing and maintaining production-grade Looker/LookML solutions - you know the difference between a good Explore and a great one.
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Comfortable with version control workflows (GitHub/GitLab) and treating the BI codebase as production software.
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We're a team that actively experiments with AI to move faster and think sharper — if you're curious about how AI tools can augment analytical work, you'll feel right at home.
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Python scripting experience for data wrangling or pipeline automation is advantageous.
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Familiarity with dbt or similar transformation tools is a strong plus.
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Business-first thinker: you don’t just build what’s asked, you ask why it’s needed and whether there’s a better way to answer the underlying question.
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Detail-oriented and rigorous — you have a zero-tolerance mindset for data quality issues and know how to build systems that catch problems early.
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Strong communicator who can translate analytical complexity into clear, actionable insights for commercial and executive stakeholders.
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Self-directed and comfortable operating in an async, remote-first environment with stakeholders across multiple time zones.
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A collaborative team player who gives and receives feedback constructively, and actively contributes to a culture of learning and continuous improvement.
- A degree in Computer Science, Statistics, Mathematics, Business, or a related field.
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