Satispay
financial platform
DataAnalyst-AnalyticsEngineering
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Analyst - Analytics Engineering at Satispay. Skills: Analytics Engineering, Data Modelling, Data Pipelines, AI-powered workflows, Data Visualization, Consumer Funnel Analysis, Stakeholder Management. Lead Design Data Architecture. Drive the development of the Data Mesh layer by designing robust data models and building pipelines that integrate into the company's federated data strategy”
What You'll Achieve.
Enhances decision-making by developing scalable data assets and AI-powered workflows; Maximise ROI; Deliver evidence-based answers
Industry & Context.
Problem-solver; Break down complex problems into focused workstreams; Deliver evidence-based answers
What They're Looking For.
Must Have
5+ years in data-related roles (Data Engineering, Analytics, BI), at least 3 years of hands-on experience in high-volume or big data environments, command of SQL, command of dbt, command of Python, Data modelling, ETL, data governance, Data Mesh implementation at scale
Nice to Have
Experience with Git, notebook-based analytics (e.g., Jupyter), Proven ability to work with AI tools, including prompting and context management, or interacting with agents programmatically via APIs, Comfortable with ambiguity, Able to break down complex problems into focused workstreams and deliver evidence-based answers, Able to independently lead initiatives across diverse business domains, translate technical findings into clear, actionable recommendations, Solid understanding of consumer lifecycle (Acquisition, Activation, Retention, Churn), Solid understanding of user economics (ARPU, CAC, LTV)
What You'll Do.
Lead Design Data Architecture
Drive the development of the Data Mesh layer by designing robust data models and building pipelines that integrate into the company's federated data strategy
Define AI Agentic Workflows
Design and implement AI-powered agentic workflows for data transformation and exploration
Build High-Impact Visualisation Tools
Define key metrics and develop dashboards and reports (using tools like Hex or Looker)
Drive Decision-Making Through Data
Analyse complex datasets to identify patterns impacting the consumer funnel (Acquisition
Drive Testing Initiatives
Own the end-to-end testing pipeline
from opportunity identification to experiment design and recommendation delivery
How You'll Work.
Team & Collaboration
Partner with Marketing Managers to maximise ROI; Act as a strategic partner for Marketing, Finance, Operations, and Product; Bridging the gap between technical data and business goals; Teamwork
Communication Scope
Communicate analytical insights effectively; Translate technical findings into clear, actionable recommendations
Process & Methodology
Independently lead initiatives
Full Job Description
About us Satispay began by rethinking the simple act of a payment to remove the friction from our daily routines. But we didn’t stop there. Today, we are building a complete financial platform designed to empower people and concretely improve their lives. By giving our 6 million users a clear, open path to pay, save, and invest, we are evolving into the definitive destination for every financial need. What you'll be doing As our Data Analyst - Analytics Engineering, you’ll be the person who drives our data strategy and enhances decision-making by developing scalable data assets and AI-powered workflows. You will join the Growth & Marketing (G&M) B2C Analytics team, which sits at the heart of our department with the mission to put intelligence first in every decision. Here's what your day-to-day will look like: - Lead Design Data Architecture – Drive the development of the Data Mesh layer by designing robust data models and building pipelines that integrate into the company's federated data strategy, ensuring scalable and governed data ownership. - Define AI Agentic Workflows – Design and implement AI-powered agentic workflows for data transformation and exploration, accelerating analytical capabilities and enabling self-service for key stakeholders. - Build High-Impact Visualisation Tools – Define key metrics and develop dashboards and reports (using tools like Hex or Looker) that communicate analytical insights effectively. - Drive Decision-Making Through Data – Analyse complex datasets to identify patterns impacting the consumer funnel (Acquisition, Engagement, Retention, Monetisation) and partner with Marketing Managers to maximise ROI. - Partner with Key Stakeholders – Act as a strategic partner for Marketing, Finance, Operations, and Product, bridging the gap between technical data and business goals. - Drive Testing Initiatives – Own the end-to-end testing pipeline, from opportunity identification to experiment design and recommendation delivery. Who we're loo
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