Sharpist is a results-oriented, digital coaching provider with the mission to drive the growth of organizations and their people through 1:1 digital coaching and personalized learning programs.…
Sharpist is a results-oriented, digital coaching provider with the mission to drive the growth of organizations and their people through 1:1 digital coaching and personalized learning programs.…
What they do: Digital coaching and leadership development (1:1, group, peer) with analytics
Founded: 2018, Berlin
Employees: 220
Recent funding: $23M Series A (Feb 15, 2022); total reported $29.2M
Security: ISO/IEC 27001:2013 certified
Company Overview
Problem Domain
Workforce leadership development, employee upskilling, and scalable coaching for enterprises.
Founded
2018
Industry
Professional Training and Coaching
Funding Track Record
Series A- 2022-02-15
$23,000,000
Participation from Vorwerk Ventures, btov Partners, Porsche Ventures, Founders Future, and selected business angels
Investor Signal
“Co-led Series A by institutional European VCs with participation from corporate and angel investors”
Founders
What we do
Join the Team
Senior Data Engineer
On-SiteBerlin, DE
On-Site • Berlin, DE
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Who you are
You are a Systems Thinker. You don't just write a query; you ask, "What happens if this data stream fails? Is this operation idempotent? How do we handle eventual consistency in the UI?"
You are a Builder. You are comfortable jumping into the backend codebase to expose your data via an API. You don't stop at the database layer
You have Engineering Rigor. You believe that data pipelines deserve the same standard of care as production software: CI/CD, Unit Tests, and Observability
Must Have: Deep experience designing data-intensive applications. You understand the CAP theorem, race conditions, and how to model data for both relational/NoSQL (MongoDB) and analytical (BigQuery) needs
Must Have: Strong programming experience is required. Ideally, you are highly proficient in TypeScript or Python, but hands-on experience building robust services in other languages is highly appreciated
Nice to Have: Experience with LLM orchestration, AI evaluation pipelines, or building recommendation/matching algorithms
What the job involves
Benefits
Have your own certified coach
Flexible working hours
Free mate, beers & muesli
Unlimited vacation policy
Language classes
Employee library
Sustainable company discounts
Visa & relocation support
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We are looking for a Senior Data Engineer with a product mindset
What does this mean? It means you are, first and foremost, a product-minded software engineer.
You care about the end-user experience and business outcomes, but your primary medium for solving those problems is data infrastructure, pipelines, and architecture
You will not be a "service bureau" answering ticket requests for SQL queries or just building internal dashboards. Instead, you will be a core builder on a stream-aligned team, treating data as production infrastructure.
You will bridge the gap between backend application engineering and data engineering to architect the systems that power our core product capabilities—such as matching users to coaches, evaluating our AI agents, and personalizing the learning journey
As a Senior Product Engineer (Data), you will own the data layer from concept to production
Finding and Implementing Key Metrics: You won't just move data around; you will partner closely with Product, Design, and Business stakeholders to figure out what we should be measuring. You will identify, define, and implement the core metrics and telemetry that track user behavior, drive product iteration, and directly impact business growth
Building Data-Intensive Product Features: You will architect and deploy the backend data engines that power our customer-facing features. This includes our real-time coach matching algorithm and the evaluation pipelines (Evals) that ensure our AI agents are accurate and safe
Engineering Enablement: Traditional Data Engineers often become bottlenecks. Your goal is to build self-service data infrastructure and abstractions. You will create the tools that allow the rest of the engineering team to independently query data, track their own metrics, and answer their own questions
Treating Data as Code: You will apply rigorous software engineering practices to our data workflows, ensuring everything is version-controlled, tested, and reliable
