How Storyclash Builds Data Products: Team Structure, Hiring, and Tech Stack — Insights from Ismail Hanli, Head of Data Acquisition

Context and overview

In the session “Ismail Hanli, Head of Data Acquisition bei Storyclash” (Speaker: Ismail Hanli, Company: Storyclash), we got a clear, no-frills look at how a data-first product organization structures its engineering teams, hires talent, and turns social-media data into value. Hanli walked us through Storyclash’s Techlead setup, the phases of their hiring process, and a technology stack that ranges from Vue.js and PHP to Python, Node.js, Redis, PostgreSQL, and CrateDB — with headless browser services playing a central role in data acquisition.

One theme tied it all together: organization and process exist to give engineers maximum focus. Techleads handle direction and guardrails; developers concentrate on building. And the product mission is explicit: understand how social platforms work, know where the data comes from, and prepare it in a way that is immediately useful to customers — so they don’t need a team of people to stitch it together manually.

Engineering organization: CTO on top, Techleads by domain

Hanli’s description of the org is short and precise: a CTO at the top, then several Techleads, each responsible for a specific domain. The domains he names include:

• Databases
• Backend crawlers
• MyPath
• The web app team
• A CMS project for internal use

The picture is one of clear responsibility: Techleads set direction and coordinate, and developers do the heavy lifting to turn plans into working software. The point of Techleads here is practical, not ornamental: reduce management overhead for those who build.

Small, focused teams — with “room for growth”

Team sizes are explicit: two to four developers per team. That’s small enough for tight communication and quick decisions, yet large enough to share ownership. Importantly, the setup is growing.

That sentence carries a clear signal: Storyclash is hiring, and it’s doing so in a way that creates space for people to grow into domains and responsibilities. For engineers who want ownership as well as impact, that’s compelling.

Why Techleads matter

The primary value of Techleads shows up in one simple effect: they create focus for deep work. Hanli puts it plainly.

In data-intensive products like Storyclash, teams must wrangle crawlers, data stores, performance and presentation. Unnecessary distractions have a real cost. The Techlead layer acts as a buffer — and as a technical center of gravity for decisions and prioritization.

Hiring on equal footing, not as a gauntlet

Hanli is unequivocal: this is the best hiring process he has experienced. The reason? Conversations at eye level.

Instead of candidates feeling like they must beg for acceptance, the focus is on mutual fit and collaboration.

He outlines the steps clearly:

1. Conversations with Techleads (including with Hanli) — early, real technical contact.
2. A coffee chat — meet a handful of team members to see if you understand one another and would actually work well together.
3. Offer — if the feeling is right, the process moves forward.

Another nuance stands out: technical ability is assumed. It’s not that skills are ignored — but they’re not the center of an obstacle course. Fit and collaboration are.

For candidates, that changes the tone entirely: conversations are about reality, not riddles.

Onboarding: “cold water,” with clear guardrails

Onboarding follows the same pragmatic line. After the initial setup days, new hires get real, pre-defined tasks — deliberately challenging but not overwhelming.

The effect is twofold: new colleagues gain a holistic view of the system fast, and time-to-first-contribution drops. In a landscape with many technologies and data flows, that’s the fastest path to genuine understanding.

The tech stack: breadth that serves the mission

Hanli lists the technologies in use, and the stack maps neatly to the demands of a system that must ingest, process, and present large volumes of social-media data.

• Frontend/web app: Vue.js
• Main application language: PHP
• Python: machine-learning applications
• Node.js: headless browser tasks
• Headless browser services: operated as standalone services
• Redis: performance layer
• PostgreSQL: database
• CrateDB: database

Headless browser services point to scalable content acquisition where APIs are insufficient or dynamic content must be rendered. Redis accelerates lookups and offloads databases. PostgreSQL and CrateDB cover different persistence and query patterns, from relational consistency to distributed workloads. Python is a natural fit for ML, and Node.js offers robust headless operations. Vue.js and PHP anchor the product experience in a productive web-app environment.

Hanli sums it up simply:

This isn’t a tool zoo. It’s purpose-driven engineering.

The product principle: understand, consolidate, prepare

Storyclash’s core is the path from raw social data to immediate customer value. Hanli frames it as three tasks: understand platforms, know where to get the data, and prepare it so that customers can use it right away.

That’s non-trivial. Platforms change interfaces and formats; relevance is contextual; data quality determines trust. Storyclash addresses this by merging large amounts of data and preparing them so that customers don’t need manual effort.

For engineering, this translates into robust crawlers, resilient pipelines, high-performance data access, and a web app that surfaces the right signals.

Collaboration: “Do we understand each other?” as a selection criterion

Hiring conversations and the coffee chat show what Storyclash prioritizes: genuine mutual understanding — technically and interpersonally. It’s not a cultural afterthought; it’s a productivity criterion. Teams building data products need clarity at boundaries and shared target pictures. Hanli puts it plainly:

That can’t be tested with a puzzle. It has to be experienced. Hence the coffee chat: real interactions with multiple team members, not a single conversation.

What tech talent can expect at Storyclash

From Hanli’s narrative, a set of concrete expectations emerges — without going beyond what’s said:

• Small, capable teams (2–4 devs) with clear responsibility.
• Techleads who absorb management overhead and provide technical direction.
• Hiring at eye level, prioritizing fit and collaboration.
• Onboarding via real tasks in “cold water,” with clear guardrails.
• A stack that covers the breadth of modern data products: Vue.js, PHP, Python, Node.js, headless browser services, Redis, PostgreSQL, CrateDB.
• A product mindset that turns data into decisions — not chores.
• Real growth signals: “We’re hiring” and “Room for growth.”

For engineers, that means practice, responsibility, and learning — with clear technical leadership.

An engineering lens on the stack

Staying strictly within what’s described, the architecture falls into place:

• Headless browsers are essential when APIs don’t expose everything or dynamic content must be rendered. Node.js is well-suited: strong tooling and patterns for parallelism.
• Redis accelerates frequent reads and supports queues for async processing.
• PostgreSQL anchors relational consistency; CrateDB adds capabilities for larger, distributed query loads.
• Python underpins ML workloads; services integrate cleanly.
• Vue.js and PHP provide a productive web-app foundation where insights are made consumable.

It’s not exotic for its own sake — it’s pragmatic and aligned with the mission.

“The best recruiting process I’ve seen”: what that implies

Three principles stand out from Hanli’s account:

• Equal footing: candidates meet the people they’ll actually work with — not just gatekeepers.
• Fit first: collaboration and mutual understanding are the main selection criteria; technical ability is assumed instead of fetishized.
• Clarity: structured steps (Techlead conversations, coffee chat, offer) without endless loops.

For candidates, that means less uncertainty and more real insight. For the team, it means better decisions and happier starts.

Onboarding that accelerates understanding

“Cold water” doesn’t mean chaos. Hanli explicitly mentions predefined tasks that stretch but don’t overwhelm. The result is rapid system-level understanding. In a multi-technology environment, that kind of early exposure is invaluable.

It’s a fast track to ownership and impact.

From raw social data to usable insights

Hanli doesn’t treat social media as just another data source; he treats it as structurally defining. Each platform behaves differently and changes quickly. That makes data acquisition and preparation not only a technical challenge but a product decision: What do customers actually need? Which metrics and contexts matter? Once that’s clear, the engineering work truly compounds in value.

The vision: less human stitching, more system-level preparation; less manual burden, more insight in the web app.

Why Storyclash is attractive to engineers

If we map Hanli’s points into reasons to join, several stand out:

• Technical focus: those who build are protected from management overhead by Techleads.
• Responsible team design: small teams, clear domains, visible impact.
• Learning through doing: onboarding via real tasks, broad stack, deep system exposure.
• Respectful process: hiring at eye level, meeting real teammates early.
• Meaningful mission: not just collecting data, but preparing it so customers immediately benefit.
• Growth: explicit signals — “We’re hiring” and “Room for growth.”

It’s an offer to do professional work with substance.

Quotable moments

• “Auf Augenhöhe die Kommunikation.”
• “Passt du zu uns und alles andere machen wir schon.”
• “Die Teamgrößen … zwei bis vier … ständig am wachsen … Wir suchen Leute … Room for growth.”
• “Als Entwickler … nicht mit Management-Sachen beschäftigt.”
• “Ins kalte Wasser … vordefinierte Aufgaben … nicht überwältigt … alles anschauen.”
• “Headless-Browser-Services … Redis … PostgreSQL … CrateDB …”
• “Social-Media-Plattformen verstehen … Daten herkriegen … aufbereiten … Mehrwert …”
• “Menge an Daten … zusammenführt … aufbereitet … präsentieren … ohne 20 Leute … manuell …”

Conclusion: Structure creates focus, focus creates productivity

“Ismail Hanli, Head of Data Acquisition bei Storyclash” makes a compelling case for aligning org design, hiring, and technology around one idea: let engineers build. With clear Techleads, small teams, and an equal-footing hiring process, Storyclash sets the stage for deep, productive technical work. The stack is broad but purposeful; the mission is plain: understand social platforms, bring the data together, and prepare it so customers can act — without manual stitching.

For talent that values impact over theatrics, that’s a strong invitation.

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