Accountabilities:

You will lead analytics delivery across assigned client accounts, ensuring that every analysis is accurate, relevant, and aligned with business priorities. You will combine advanced technical skills with strong stakeholder management to turn data requests into meaningful insights and measurable recommendations.

Analytics Ownership & Client Collaboration

Own the analytics workstream for assigned accounts, managing request intake and prioritization within agreed working hours.

Act as the primary point of contact for client data and analytics questions, ensuring requests are clearly framed and based on sound assumptions.

Identify when requests exceed the agreed scope or require a dedicated project, communicating this proactively to relevant stakeholders.

Collaborate with Lead and Senior Consultants, Account Management, and Project Management, as well as client marketing, loyalty, and data teams.

Manage analytical assignments independently, from initial client request through final presentation and recommendations.

Data Analysis & Technical Execution

Write production-quality SQL in client data warehouses such as Snowflake, Databricks, Redshift, or equivalent platforms.

Develop the transformation logic required to support reliable analysis and reporting.

Trace data lineage, identify and resolve gaps in existing reports, SQL queries, and data events.

Reconcile metrics across different systems, including product and digital analytics platforms such as Amplitude and Google Analytics 4.

Conduct cohort, behavioral, and decomposition analyses using customer, transaction, and loyalty data.

Analyze key commercial metrics, including first and repeat purchases, average transaction value, revenue, purchase frequency, retention, lifetime value, and offer performance.

Build or leverage propensity and segmentation models to identify customer opportunities and improve targeting.

Connect insights across customer segments, offers, channels, and seasonality to revenue growth, operational efficiency, and cost savings.

Experimentation & Performance Measurement

Independently design and report on experiments, including sample size calculations, holdout group design, and incremental uplift measurement.

Analyze test results and performance variations across customer segments.

Use AI tools to accelerate analytical workflows, improve testing efficiency, and strengthen the quality of insights.

Reporting, Dashboards & Data Quality

Build and maintain dashboards using business intelligence platforms such as Power BI, Tableau, Looker, or equivalent tools.

Define, document, and maintain the KPIs and measurement logic behind reporting solutions.

Validate and document all figures before sharing results with clients or internal stakeholders.

Present analytical findings and recommendations through clear, compelling, and strategic narratives tailored to senior and non-technical audiences.

Team Development & Knowledge Sharing

Review other analysts' SQL and provide guidance on analytical quality and best practices.

Coach consultants on using data effectively to support client recommendations.

Manage and mentor one to two junior analysts as the team expands.

Develop reusable analytical assets, frameworks, and reporting approaches that can be applied across multiple client accounts.

Requirements:

The ideal candidate combines advanced SQL and data analytics expertise with strong commercial awareness and the ability to communicate confidently with clients. You should be comfortable owning analytical projects independently, challenging assumptions, and translating complex findings into practical business recommendations.

Strong experience writing production-quality SQL in Snowflake or another cloud data warehouse, such as Databricks or Amazon Redshift.

Experience building dashboards and reporting solutions using BI tools such as Power BI, Tableau, or similar platforms.

Advanced Excel skills.

Experience with product or digital analytics platforms such as Amplitude, Google Analytics 4, or Mixpanel.

Hands-on experience conducting cohort and behavioral analyses using customer, transaction, or loyalty data.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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