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full stack engineer

senior data engineer

(senior) data engineer (gn) Jobs in Berlin

(senior) data engineer (gn)

ai engineer — genai & agentic solutions (m/w/d) amazon web services Jobs in Berlin

data engineer

Talon.One LinkedIn Jobs

<div><div><p><b>ABOUT TALON.ONE:</b></p><br>
<p></p>
<p>
Talon.One is the most powerful incentives engine that unifies loyalty, promotions and gamification into one holistic platform. Backed by enterprise-grade security and scalability, Talon.One empowers companies to build personalized, profitable promotions and loyalty programs using any data.</p>
<p>
Today, over 250 of the world's most-loved brands including Adidas, Sephora and Carlsberg work with Talon.One to drive deeper engagement and lasting loyalty with their customers.</p></div><br>
<p></p>
<p><b>
ABOUT THE TEAM:</b></p>
<p>
We're a passionate team, consisting of a Head of Data, a Data Engineer, an Analytics Engineer and a Senior Data Analyst dedicated to all things data. You'll be at the centre of our expanding Data team. We're enthusiastic about exploring new tools and technologies, and we thrive on brainstorming to solve challenges and apply best practices. Our team is set to grow soon, welcoming Data Engineers, Analytics Engineers, Analysts, and Data Scientists, all playing a pivotal role in Talon.One's development.</p>
<p><b>
ABOUT THE ROLE:</b></p>
<p>
As a Senior Data Engineer / Data Ops, you will be responsible for all engineering tasks related to the data infrastructure, data ingestion and DWH pipelines. You will own our data ingestion workflows (currently based on a Kafka stream) and will make sure that the data from our PostgresDB instances with a very high amount of data is ingested live into BigQuery. Besides, you will manage our overall data platform infrastructure, recommend improvement and make sure to always follow best practices. Finally, you will also of course be involved in the Data Engineering pipelines, assisting in the modelling of various data sources helping literally all departments within the company making better decisions.</p><br>
<p></p>
<p><b>
ONCE YOU ARE HERE YOU WILL:</b></p><br>
<p></p>
<ul>
<li>Own the data ingestion streams for all of our client's DBs, from Postgres to BigQuery</li>
<li>Own the overall data infrastructure: set up, maintain and improve our stack with new technologies for more efficiency and best practices. E.g. improve orchestration</li>
<li>Write DWH pipelines and improve our overall DWH code to apply best practices and bring more efficiency.</li>
<li>Be part of a data team composed of various profiles, be at the center of all infrastructure decisions and work closely with other stakeholders from the R&amp;D department, especially the DevOps team.</li>
</ul>
<p><b>WHAT WE NEED YOU TO BRING TO THE TABLE:</b></p>
<ul>
<li>3 -5 years of experience in the Data Engineering / Data Ops field, ideally working on some big data warehouse projects.</li>
<li>You are familiar with the modern data stack and are able to recommend, set up and maintain all different kinds of components from Data ingestion to automation.</li>
<li>You have experience with a wide range of tools and technologies within the modern data stack: Kafka, Airflow, Dagster, DBT Core, BigQuery, Lambda functions etc..</li>
<li>You have experience with general infrastructure / DevOps management technologies: ArgoCD, Kubernetes, Docker, Github, Postgres, GCP etc..</li>
<li>You always thrive for applying data engineering best practices: consistency checks, testing data reliability, monitoring on top of ingestion pipelines, no double business logic in the code.</li></ul><br>
<p></p>
<p><b>
ABOUT TECHNOLOGY:</b></p>
<ul>
<li>Kubernetes running on Google Cloud, ArgoCD, Terraform</li>
<li>PostgreSQL</li>
<li>Aiven Kafka Connect, Strimzi, Debezium</li>
<li>DBT cloud, GCP, BigQuery, Fivetran</li>
<li>We use Go for our API, core logic, and internal tooling</li>
<li>Cypress for automated end-to-end testing</li>
<li>Other odds &amp; ends in JavaScript and shell script</li></ul><br>
<p></p>
<div><b>
WHAT'S IN IT FOR YOU:</b></div>
<ul><li>A Research and Development Department of 90+ of engineers, product managers and product designers in Berlin</li>
<li>Leaders with 8+ years of experience building our promotions engine</li>
<li>&euro;1,000 annual learning budget and free German language courses to boost your skills</li>
<li>30 days of annual leave, plus extra paid days for your birthday and moving day</li>
<li>Home office setup budget, a monthly home office allowance</li>
<li>Freedom to work from abroad for up to 90 days worldwide!</li>
<li>Mental health support with nilo.health and a discounted Urban Sports Club membership</li>
<li>20% company subsidy on your pension contributions</li>
<li>Subsidised BVG public transport ticket and a dog-friendly Berlin office where your furry friend is welcome</li>
<li>Lease your ideal bike through BusinessBike</li></ul></div><p></p>

Senior Data Engineer

Future Energy Services GmbH

<div><h1 class="jobSectionHeader"><b>Senior Data Engineer</b></h1><div></div><div><br>
</div><h2 class="jobSectionHeader"><b>
About trawa</b></h2><div></div><p><br>
European energy costs are twice as high as in the United States and China. Electricity demand is expected to double by 2050. Market price volatility and complexity are here to stay - and the backbone of Europe's industrial economy is at risk.</p><div></div><p><br>
At trawa, we're building the solution: an integrated B2B energy platform combining procurement, energy management, and flexibility steering in a single product. That integration unlocks up to 30% in recurring electricity cost savings while helping companies make the switch to renewables.</p><div></div><p><br>
We're a Berlin-based scale-up of around 100 people. We've raised over &euro;35M to date - including a &euro;24M Series A in May 2025 - backed by Balderton, Headline, Speedinvest, AENU, Magnetic, and Tiny VC. All three founders are fully committed to building the utility of the future.</p><div></div><div><br>
</div><h2 class="jobSectionHeader"><b>
The Team</b></h2><div></div><p><b><br>
Data Intelligence (DINTEL)</b> is an engineering team that owns trawa's data pipelines, and analytics infrastructure. We manage the full data lifecycle - from ingesting raw metering and market data, to invoicing and self-service analytics.</p><div></div><div><br>
</div><h2 class="jobSectionHeader"><b>
About the Role</b></h2><div></div><p><br>
We're looking for a <b>Senior Data Engineer</b> to own and lead the development, reliability, and continuous evolution of our data platform. This is a high-ownership, high-autonomy role. You'll work across production systems at scale - defining technical direction, coordinating cross-team dependencies, and driving measurable impact across data engineering, analytics infrastructure, and operational tooling.</p><p>
You'll mentor teammates and be supported by experienced engineering leaders as you continue to grow your own leadership and technical skills.<br>
<br>
This role follows a hybrid working model. We expect team members to spend around 2-3 days per week in our Berlin office. There are no fixed office days and we don't monitor attendance strictly, but regular in-person collaboration is an important part of how we work.</p><div></div><div><br>
</div><h2 class="jobSectionHeader"><b>
What You'll Do</b></h2><div></div><ul><li><p><br>
Lead the design, implementation, and operation of critical data pipelines and platform infrastructure on AWS</p></li><li><p>
Define and evolve data quality standards, observability practices, and operational controls across the platform</p></li><li><p>
Lead cross-team technical discussions and help align stakeholders on data platform architecture decisions</p></li><li><p>
Deliver large-scale technical initiatives end-to-end, from design through delivery, collaborating with teams across the business</p></li><li><p>
Shape the team's technical culture through code reviews, mentorship, knowledge sharing, and documentation</p></li><li><p>
Evolve our analytics and BI tooling (ClickHouse, Metabase) to support business intelligence and decision-making</p></li><li><p>
Build and maintain data pipelines using Python (pandas, polars), dbt, and dlt</p></li><li><p>
Identify and address technical debt, improving platform reliability, scalability, and developer experience</p></li><li><p>
Communicate the value and impact of platform improvements to engineering and business stakeholders</p></li><li><p>
Diagnose and resolve complex data and performance challenges across multiple systems and services</p></li></ul><div></div><div><br>
</div><h2 class="jobSectionHeader"><b>
Your First 90 Days</b></h2><div>
</div><h3 class="jobSectionHeader"><b>
First 6 Weeks - Getting Oriented</b></h3><ul><li><p>
Build context across the data platform, including AWS, dbt, dlt, PostgreSQL, ClickHouse, and Python services</p></li><li><p>
Begin contributing to production systems and taking ownership of key platform components</p></li><li><p>
Build relationships with engineers and stakeholders across the business to understand data needs, priorities, and opportunities for improvement</p></li></ul><h3 class="jobSectionHeader"><b>
By Month 3 - Building Momentum</b></h3><ul><li><p>
Take ownership of significant platform components and drive improvements with growing independence</p></li><li><p>
Begin leading a cross-team initiative with support from your manager and teammates, helping align stakeholders around a clear plan</p></li><li><p>
Identify and begin implementing a meaningful improvement to platform reliability, observability, or scalability</p></li></ul><div></div><div><br>
</div><h2 class="jobSectionHeader"><b>
What You'll Gain</b></h2><div></div><ul><li><p><br>
Ownership of a production data platform that directly powers trawa's energy trading, invoicing, and analytics</p></li><li><p>
The opportunity to work closely with engineering and business stakeholders on high-impact initiatives with company-wide visibility</p></li><li><p>
A chance to shape technical culture and contribute to the evolution of engineering practices across the Data Intelligence team</p></li><li><p>
Deep expertise across a modern data stack, including AWS, Python (pandas, polars, FastAPI), dbt, dlt, PostgreSQL, ClickHouse, and Metabase</p></li><li><p>
Support in growing your technical and leadership skills, with a clear progression framework and meaningful opportunities for advancement</p></li></ul><div></div><div><br>
</div><h2 class="jobSectionHeader"><b>
What We're Looking For</b></h2><p><br>
We know that great candidates don't always match every requirement. If you're excited about the role and believe you can contribute to our mission, we'd love to hear from you, even if your experience doesn't perfectly align with every qualification listed.</p><h2 class="jobSectionHeader"><b><br>
Core Requirements</b></h2><ul><li><p>
5+ years of experience in data engineering or a related field</p></li><li><p>
Strong SQL and Python skills</p></li><li><p>
Experience building and operating production data systems</p></li><li><p>
Experience collaborating across teams to deliver technical projects</p></li></ul><div><br>
</div><h2 class="jobSectionHeader"><b>
Nice to have</b></h2><div></div><ul><li><p><br>
Hands-on experience with parts of our stack, including dbt, dlt, ClickHouse, PostgreSQL, Metabase, or AWS</p></li><li><p>
Experience with workflow orchestration tools such as Airflow</p></li><li><p>
Familiarity with energy markets, time-series data, or operational data platforms</p></li><li><p>
Experience in a technical leadership role</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
What Helps You Succeed Here</b></h2><ul><li><p>
Experience designing scalable and reliable data systems</p></li><li><p>
Enjoy mentoring and supporting the growth of teammates</p></li><li><p>
Comfort navigating ambiguity and helping bring clarity to complex problems</p></li><li><p>
Strong communication and stakeholder-management skills</p></li></ul><div></div><div><br>
</div><h2 class="jobSectionHeader"><b>
Why Join Us</b></h2><div></div><p><br>
<b>Real impact</b> - Join one of Europe's fastest-growing B2B energy platforms at a pivotal moment. Your work will directly support systems that help industrial companies cut costs and go green.</p><div></div><p><br>
<b>Early ownership</b> - We give team members responsibility from day one. You won't be shadowing - you'll be shipping.</p><div></div><p><br>
<b>Mentorship that matters</b> - Regular leadership sessions, cross-functional exposure, and engineers who are genuinely invested in your growth.</p><div></div><p><br>
<b>Learning culture</b> - Annual learning budget, dedicated development time, and a team that takes knowledge-sharing seriously.</p><div></div><p><br>
<b>Inclusive by design</b> - 15+ nationalities, family-friendly policies, and a genuine commitment to building a place where everyone can do their best work.</p><div></div><p><br>
<b>Solid benefits</b> - A competitive package covering wellbeing, learning, and team experiences.</p></div>

The Quality Group

<p></p><div><p>Start: Immediately | Level: Mid - Senior | Location: Germany, remote | Working Hours: Full Time (40h/Week)</p><br>
<p>
We're looking for a (Senior) Data Engineer (gn) who's ready to leave a real mark. You'll take ownership of our data platform, drive the architecture of scalable and reliable data products &ndash; and play a central role in shaping our Data Warehouse to the next level. As the core of our data hub, you'll connect teams, technologies, and insights, setting the technical direction for how we work with data across the entire organisation.</p>
<h3 class="jobSectionHeader"><b>
Your mission</b></h3>
<ul><li>You design and own the architecture of our end-to-end data platform, including ingestion, transformation, and serving layers</li>
<li>You lead the development of robust data pipelines using Fivetran, Airbyte, and Python &ndash; setting engineering standards for the team</li>
<li>You drive data modeling excellence in Databricks using advanced SQL, dbt, and data quality frameworks like elementary</li>
<li>You define and enforce data quality standards, ensuring reliable data marts that power business-critical decisions</li>
<li>You act as technical lead, collaborating closely with the Product Owner and Business Insights team on complex data challenges</li>
<li>You own and evolve our cloud infrastructure on AWS, driving infrastructure-as-code with Terraform (IaC)</li></ul><p><br>
</p><h3 class="jobSectionHeader"><b>Your experience &amp; skills</b></h3>
<ul><li>You have several years of hands-on experience as a Data Engineer, ideally in a cloud-native environment</li>
<li>You're proficient in SQL, Python, dbt, and Git &ndash; and have a strong track record of building production-grade pipelines</li>
<li>You bring experience with cloud platforms (AWS preferred) and tools like Databricks, Fivetran, or Airbyte</li>
<li>You have a deep understanding of data modeling, data warehouse design, and data quality best practices</li>
<li>You're a strong communicator who can bridge the gap between engineering and business stakeholders</li>
<li>You're self-driven, take ownership end-to-end, and thrive in a remote, async-first environment</li>
</ul><h3 class="jobSectionHeader"><b>Why choose us?</b></h3>
<p>
Being part of our team means joining a high-performing company with a diverse and inclusive culture. In our fast-growing team of over 1,200 employees, we combine our passion for sports nutrition, supplements, and healthy foods with cutting-edge technology, production, and logistics processes. All of this serves one goal: providing our customers with top-quality products to support their healthy and active lifestyle.</p>
<p>
You can look forward to a strong sense of team spirit, ongoing opportunities for professional growth and responsibility, and an exciting work environment that blends lifestyle and career. With locations in Hamburg, Elmshorn, Kaltenkirchen/N&uuml;tzen, and Elsdorf, TQG offers diverse career opportunities in areas such as technology, product development, sales, marketing, and logistics. Additionally, you'll benefit from:</p>
<ul>
<li>Flexible working hours and remote work options</li>
<li>Attractive employee discounts</li>
<li>Subsidy for the E-gym Wellpass</li>
<li>Workation</li>
<li>Corporate benefits</li>
<li>28 days vacation/year</li>
<li>and much more</li></ul><br>
<p></p>
<h3 class="jobSectionHeader"><b>
About Us</b></h3>
<p>
The Quality Group (TQG) is an innovative provider of sports nutrition products, bringing together the successful brands <b>ESN </b>and <b>More Nutrition </b>since 2021.</p>
<p><b>
ESN </b>has been the German market leader in sports nutrition since 2004, offering products like protein powders, bars, and supplements designed for ambitious fitness goals. Founded in 2017, <b>More Nutrition</b> focuses on healthy, reduced-sugar foods, providing solutions for conscious nutrition and weight management without compromise.</p>
<p>
TQG's vision is to help people become the best version of themselves. With passion and innovation, the company develops high-quality products that promote health, performance, and joy in life. Its agile company culture and exciting career opportunities make TQG a strong partner not only for customers but also for employees.</p>
<p><b>
This is us &ndash; The Quality Group &ndash; nice to meet you! Now it's your turn!</b><br>
We look forward to your application! Regardless of gender, age, background, or identity &ndash; what matters to us is who you are and what you bring to the table. Join our team and grow with us!</p></div><p></p>

(Senior) Data Engineer (gn)

Saas.group

<div><p>This role is part of our INFOnline team, one of our exciting brands at saas.group.</p>
<p>
INFOnline powers digital audience measurement for the German and Austrian media industry. Our systems process billions of events and deliver the trusted reach and engagement metrics used by publishers, advertisers, agencies, IVW and OEWA.</p>
<p>
As part of saas.group, we have been modernizing our business-critical infrastructure and moving towards a fully cloud-native architecture on GCP. The major migration work is complete. Now we are looking for a strong technical owner to run, harden, scale and evolve the new platform.</p>
<h3 class="jobSectionHeader"><b>
Profile Overview</b></h3>
<p>
We're looking for a technically deep, hands-on Lead Data Platform Engineer to take full ownership of INFOnline's central data platform from raw event ingress through processing, aggregation, data modeling and reporting delivery.</p>
<p>
You will take ownership of a newly built GCP-native data platform as it moves from completed migration into long-term production operation, optimization and continuous evolution.</p>
<p>
This is not a role where you simply follow someone else's roadmap. You will help define how the platform should mature: where we need stronger observability, better data quality controls, clearer ownership boundaries, improved documentation, cost efficiency and more scalable operating models.</p>
<p>
This is a hands-on technical leadership role. You will set technical direction, make architecture decisions, establish engineering standards, mentor others and still work close to the code and systems.</p>
<p>
On top of that, you will help drive AI-native engineering practices using coding agents, AI-assisted testing, documentation, refactoring and incident analysis to increase engineering speed and quality.</p>
<h3 class="jobSectionHeader"><b>
Your immediate impact in the first 3-6 months will be:</b></h3>
<ul><li>Audit and map the existing cloud and data platform architecture identify critical risks, dependencies, and improvement opportunities</li>
<li>Take ownership of core platform components from data ingress to reporting, supported by structured knowledge transfer where needed</li>
<li>Establish full internal ownership of the new cloud-native data platform</li>
<li>Improve data quality controls, validation processes and operational safeguards</li>
<li>Build a pragmatic post-migration roadmap focused on stability, scalability, data quality, cost efficiency and business continuity</li>
<li>Strengthen monitoring, alerting, and observability for business-critical data workflows and IVW/OEWA delivery pipelines</li>
<li>Establish engineering standards around documentation, code reviews, testing and AI-native development practices</li>
</ul><h3 class="jobSectionHeader"><b>Your responsibilities</b></h3>
<ul><li>Own the end-to-end data platform roadmap and drive its execution from architecture decisions to day-to-day platform operations</li>
<li>Take accountability for data ingress, streaming processing, batch aggregation, data modeling, quality, delivery and reporting logic</li>
<li>Ensure reliability, scalability and performance through strong monitoring, observability and incident management practices</li>
<li>Continuously improve the new GCP-native platform with a focus on stability, cost efficiency, maintainability and business continuity</li>
<li>Collaborate closely with Product, Customer Success and Leadership to translate business requirements into scalable technical solutions</li>
<li>Drive AI-native engineering adoption, including AI-assisted coding, refactoring, testing, documentation and code reviews and establish standards for safe, effective use</li>
<li>Work with external specialists where useful and establish sustainable internal ownership of all critical platform components</li>
</ul><h3 class="jobSectionHeader"><b>What You bring to the table</b></h3>
<ul><li>5+ years of experience in Data Engineering, Data Platform Engineering, or Platform Engineering in production environments</li>
<li>Solid Go (Golang) proficiency is required. Our core backend systems, including ingress collectors, Pub/Sub processors, Dataflow jobs, batch loaders, controllers and CLI tools are written in Go.</li>
<li>Strong hands-on experience with GCP Cloud Run, Pub/Sub, BigQuery, Dataflow, Cloud Storage, Cloud SQL</li>
<li>Strong SQL and analytical data modeling skills; familiarity with SQLMesh (or similar dbt-style orchestration tools) is a significant plus</li>
<li>Practical experience with Terraform / IaC, CI/CD pipelines, and containerized workloads (Docker; Cloud Run-style serverless, not cluster Kubernetes)</li>
<li>Experience with Protobuf or comparable schema definition and serialization frameworks</li>
<li>Familiarity with IVW, OEWA or comparable digital audience measurement standards or a genuine interest in the web analytics domain and the ability to ramp quickly</li>
<li>Experience with AI coding assistants and coding agents (Claude Code, Codex, or similar) and sound judgment in reviewing AI-generated code for quality, security, and operational risk</li>
<li>Excellent communication skills with both technical and non-technical stakeholders</li>
<li>Fluent German (C1) required; good English for technical documentation and saas.group collaboration</li>
</ul><h3 class="jobSectionHeader"><b>What's in it for You</b></h3>
<ul><li>Ultimate flexibility: We're 100% remote. You can work from wherever you like, whenever you like.</li>
<li>Freedom and autonomy: We're a high-trust team, and you'll be given lots of flexibility to solve problems in your own way, with plenty of help from the team when you need it.</li>
<li>Minimum bureaucracy: We don't like to get bogged down with meetings and red tape. We like to be efficient and keep momentum steady &amp; sustainable.</li>
<li>Small &amp; friendly team: We help each other out, have fun, and joke around.</li>
<li>Our network: We are a community of entrepreneurial SaaS professionals that regularly exchange ideas, knowledge, learning and expertise with each other internally.</li>
</ul>
<p>INFOnline is part of saas.group and we have a shared goal of succeeding together.</p><div><p>
&mdash;</p>
<p><i>
saas.group is committed to creating a diverse and inclusive workplace. We are proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We celebrate diversity and are committed to creating an inclusive environment for all employees. If you're passionate about working with a team that values innovation, excellence, and fairness, we encourage you to apply.</i></p>
<p><i>
We believe in fair and transparent pay. Salary ranges at saas.group are location-adjusted, targeting local market medians for a remote-first environment, and will be shared with our potential future employees in writing before your first interview - so you have everything you need to evaluate the opportunity.</i></p></div></div>

Lead Data Platform Engineer (German Speaker)

Team Passerelle

<div><p>Wir sind das Team Passerelle, eine 2025 in Berlin gegr&uuml;ndete KI-Beratung aus dem gewerkschaftlichen Umfeld. Unser Name ist Programm: <i>Passerelle</i> bedeutet Br&uuml;cke. Wir sind angetreten, um inmitten der gr&ouml;&szlig;ten Transformation der Arbeitswelt genau diese Br&uuml;cke in die Zukunft zu bauen - eine Br&uuml;cke, die echten technologischen Fortschritt erm&ouml;glicht und gleichzeitig bessere Arbeitsbedingungen schafft. All das machen wir unter dem Leitsatz: Gute KI. Gute Arbeit.</p>
<p>
Gegr&uuml;ndet von erfahrenen K&ouml;pfen aus der Tech- und Beratungswelt sowie der angewandten KI-Wissenschaft, verbinden wir strategischen C-Level-Weitblick mit tiefem technologischem Sachverstand. Wir begleiten Organisationen und Institutionen auf ihrem Weg in eine KI-gepr&auml;gte Zukunft, von der strategischen Beratung &uuml;ber die werteorientierte technische Implementierung bis zur nachhaltigen Adoption im Betrieb. Neben unseren Transformationsmandaten entwickeln wir au&szlig;erdem eigene Software-Produkte f&uuml;r digitale Souver&auml;nit&auml;t.</p>
<h2 class="jobSectionHeader"><b>
Aufgaben</b></h2>
<p>
Als Data &amp; AI Engineer schaffst du bei uns die zwingende technische Voraussetzung f&uuml;r jeden erfolgreichen KI-Einsatz: eine belastbare und strukturierte Datenbasis. Dein Schwerpunkt liegt darauf, historisch gewachsene, heterogene Datenlandschaften zu erschlie&szlig;en und f&uuml;r moderne KI-Anwendungen, insbesondere Retrieval-Systeme, nutzbar zu machen.</p>
<p>
Als eine:r der ersten dedizierten Engineering-Hires gestaltest du den Aufbau unserer technischen Umsetzungskraft mit &ndash; eng an der Seite unseres AI Solutions Architect. Dein T&auml;tigkeitsfeld umfasst zwei Bereiche: In unseren Beratungsmandaten analysierst du die bestehende Datenarchitektur, deckst L&uuml;cken auf und legst das Fundament f&uuml;r die KI-Strategie. Parallel dazu entwickelst du die Daten- und Retrieval-Pipelines f&uuml;r unsere eigene KI-Infrastruktur und Software-Produkte.</p>
<p>
**<br>
Deine Aufgaben**</p>
<ul>
<li><b>Datenbestandsaufnahme &amp; Reifegrad:</b> Du erstellst Datenlandkarten &uuml;ber heterogene Best&auml;nde hinweg und bewertest den Reifegrad des digitalen Fundaments. Deine L&uuml;ckenanalysen zu Identifikatoren und Metadaten zeigen pr&auml;zise, wo der Hebel liegt.</li>
<li><b>AI Data Ingestion (KI-Enablement):</b> Du erschlie&szlig;t unstrukturierte Datenquellen (PDFs, Berichte, Publikationen) f&uuml;r die Nutzung in KI-Systemen &ndash; Text-Extraktion, Chunking-Strategien, Metadaten-Generierung, z. B. mit Werkzeugen wie LlamaParse oder Unstructuredio.</li>
<li><b>Datenfundament &amp; Retrieval:</b> Du entwickelst Metadaten- und Identifikatorkonzepte, Datenmodelle und Embedding-Pipelines und baust die Retrieval-Grundlage f&uuml;r RAG-Anwendungen &ndash; inklusive Bef&uuml;llung und Betrieb von Vektordatenbanken (z. B. Qdrant, Weaviate, pgvector). Die Qualit&auml;t dieser Grundlage bewertest du systematisch.</li>
<li><b>Datenschutz &amp; Souver&auml;nit&auml;t:</b> Du gehst verantwortungsvoll mit sensiblen Daten um und stimmst dich eng zu AI-Governance-, Datenschutz, EU AI Act und Souver&auml;nit&auml;tsanforderungen ab. Datensparsamkeit und Schutzw&uuml;rdigkeit denkst du von Anfang an mit.</li>
<li><b>Pipelines f&uuml;r interne Software-Entwicklung:</b> Du baust und betreibst perspektivisch die Ingest- und Retrieval-Pipelines f&uuml;r eigene Software-Produkte &ndash; mit DataOps-Mindset (Versioning, Testing, Observability) und einem Verst&auml;ndnis agentischer Muster inkl. Human-in-the-loop.</li>
</ul><h2 class="jobSectionHeader"><b>Qualifikation</b></h2>
<ul><li><b>Fundierte Data-Engineering-Erfahrung:</b> Mehrj&auml;hrige (3+ Jahre) im Data Engineering oder als Data Platform Engineer &ndash; idealerweise in gewachsenen, heterogenen Datenlandschaften. Exzellentes Python und SQL sowie sicherer Umgang mit dem Modern Data Stack (z. B. dbt, Airflow, Dagster) und ETL-/ELT-Prozessen.</li>
<li><b>KI-Enablement:</b> Praktische Erfahrung mit Embedding-Pipelines und Vektordatenbanken (z. B. Qdrant, Weaviate, Milvus, pgvector), ein Gesp&uuml;r f&uuml;r Retrieval-Strategien und Erfahrung mit der Erschlie&szlig;ung unstrukturierter Daten (z. B. LlamaParse, Unstructuredio).</li>
<li><b>Datenschutz-Bewusstsein:</b> Erfahrung im verantwortungsvollen Umgang mit sensiblen und personenbezogenen Daten sowie Kenntnis der einschl&auml;gigen Anforderungen (insb. DSGVO, EU-AI-Act-Awareness).</li>
<li><b>Pragmatismus bei realer Datenlage:</b> Du f&uuml;hlst dich in unvollst&auml;ndigen, gewachsenen Datenbest&auml;nden wohl und wei&szlig;t, dass ein nutzbares Datenmodell mehr wert ist als ein perfektes. Du priorisierst, wo es z&auml;hlt.</li>
<li><b>Kommunikationsst&auml;rke &amp; Haltung:</b> Du &uuml;bersetzt die Datenrealit&auml;t verst&auml;ndlich f&uuml;r nicht-technische Stakeholder und kommunizierst auf Augenh&ouml;he mit Fachbereichen. Dein Deutsch und Englisch ist verhandlungssicher. Du steuerst dich selbst, denkst l&ouml;sungsorientiert und teilst unsere Werte rund um eine gerechte Arbeitswelt von morgen.</li>
</ul>
<p><b>Sch&ouml;n, wenn du zus&auml;tzlich mitbringst:</b> Erfahrung mit Knowledge Graphs, Semantic Layer oder Text-to-SQL; ausgepr&auml;gtes DataOps-Mindset; Lust an PoCs mitzubauen</p>
<h2 class="jobSectionHeader"><b>
Benefits</b></h2>
<ul><li><b>Echter Impact &amp; Haltung:</b> Ein Arbeitsumfeld, das technologische Innovation mit gesellschaftlicher Verantwortung und nachhaltigen Werten verbindet. Du gestaltest die KI-Transformation an vorderster Front nach europ&auml;ischen, demokratischen Werten.</li>
<li><b>Sichtbarkeit &amp; Netzwerk:</b> Einblicke in hochkar&auml;tige Mandate aus Politik, Wirtschaft und Gewerkschaften</li>
<li><b>Hohe Autonomie:</b> Flache Strukturen, die bewusste Abwesenheit von Mikromanagement und echte Verantwortung f&uuml;r deine Accounts und Themen</li>
<li><b>Flexibles Set-up:</b> Remote-first mit einem Kernteam in Berlin sowie flexiblen Arbeitszeiten, die zu deinem Leben passen.</li>
<li><b>Standards:</b> 30 Tage Urlaub, ein eigenes Weiterbildungsbudget und modernste Arbeitsausstattung</li>
<li><b>Faire Verg&uuml;tung:</b> Ein transparentes Gehaltsband von 80.000 bis 95.000 &euro; brutto p.a. auf Basis einer 40h Woche (je nach Erfahrung)</li>
</ul>
<ul><li><b>Langfristige Perspektive:</b> Die Stelle ist aufgrund unserer agilen Startup-Phase zun&auml;chst auf ein Jahr befristet. Da wir uns im nachhaltigen Aufbau befinden, ist eine langfristige Zusammenarbeit unser klares Ziel. Eine Verl&auml;ngerung oder Entfristung wird bei entsprechender Mandats- und Gesch&auml;ftsentwicklung ausdr&uuml;cklich angestrebt.</li></ul>
<p><i>
Der Kern unserer Arbeit ist die sozialpartnerschaftliche Gestaltung der KI-Transformation - von der fairen Verteilung von Produktivit&auml;tsgewinnen &uuml;ber die digitale Souver&auml;nit&auml;t bis hin zur Frage, wie wir eine gerechte Arbeitswelt von morgen bauen. Wir brennen f&uuml;r diese Themen und wollen diese Br&uuml;cke in die Zukunft nicht nur theoretisch durchdenken, sondern ganz praktisch bauen.</i></p>
<p><i>
Daf&uuml;r suchen wir kluge K&ouml;pfe mit Haltung und Can-Do-Attitude, die um die Ecke denken und keine Angst haben, Annahmen zu hinterfragen. Bewirb dich ausdr&uuml;cklich auch dann, wenn dein Lebenslauf nicht perfekt auf die Beschreibung passt - f&uuml;r uns z&auml;hlen deine Perspektive und dein innerer Antrieb weit mehr als ein l&uuml;ckenloses Profil. Wenn du Lust hast, ein junges Unternehmen mitzupr&auml;gen und der Zukunft der Arbeit deinen Stempel aufzudr&uuml;cken:</i> <b><i>Join us!</i></b></p></div>

Data & AI Engineer (m/w/d)

adsquare GmbH

<div><div>Berlin</div><div>
Full-time</div><div>
Permanent employee</div><div>
60,000 - 75,000 &euro; per year</div></div>
<br><div><div><h2 class="jobSectionHeader"><b>Intro</b></h2><div><div>
At Adsquare, our mission is driven by our core focus: <b>Passion</b> &ndash; Solving complex challenges with great people, tech, and data. <b>Niche</b> &ndash; Location Intelligence for Programmatic Advertisers. Our core values are integral to everything we do:</div><ul><li><div><b><br>
Drive:</b> We turn ambition into action.</div></li><li><div><b>
Resilience:</b> We adapt, persevere, and grow stronger.</div></li><li><div><b>
No BS:</b> We value honesty, transparency, and clear communication.</div></li><li><div><b>
Humble:</b> We choose modesty over vanity and let results speak for themselves.</div></li><li><p><b>
Moral Compass:</b> We do the right thing with fairness, integrity, and respect.</p></li></ul><div>
We seek candidates who not only bring excellent technical expertise but also embody these values in every aspect of their work.</div></div></div><div><h2 class="jobSectionHeader"><b>
Your Mission</b></h2><div><div><b>
Key Responsibilities</b></div><ul><li><div><b><br>
Pipeline Engineering:</b> Build, deploy, and maintain robust transformation pipelines for high-volume data. You will participate in the full lifecycle: ingestion, transformation, <b>testing (unit/integration)</b>, deployment, and monitoring.</div></li><li><div><b>
Optimization &amp; Maintenance:</b> Write highly efficient code and collaborate with the team to refactor legacy systems, helping to improve performance and reduce cloud compute costs (e.g., optimizing Athena/Snowflake/Redshift clustering or AWS Glue jobs).</div></li><li><div><b>
Software Engineering Best Practices:</b> Adhere to and promote the team's technical standards by actively utilizing CI/CD workflows, containerization (Docker), and automated testing.</div></li><li><div><b>
Data Quality &amp; Observability:</b> Focus on infrastructure monitoring rather than just business dashboards. You will implement alerts and checks (e.g., dbt tests, Great Expectations) to catch data quality issues before they reach stakeholders.</div></li><li><p><b>
Collaboration &amp; Growth:</b> Work closely with Senior Engineers to plan architectures, participate actively in code reviews, and advocate for engineering rigor within the squad.</p></li></ul></div></div><div><h2 class="jobSectionHeader"><b>
Your Profile</b></h2><div><div>
We are looking for a <b>Data Analytics Engineer</b> who approaches data with a software engineering mindset. You will join our Data Solutions squad to build and maintain production-grade data platforms.</div><div><b>
This is not a Data Analyst role.</b> While you will understand the business context, your primary focus is technical: building scalable workflows, writing clean and testable Python/SQL code, automating deployments, and supporting cloud infrastructure optimizations. You will ensure our pipelines remain reliable, cost-effective, and maintainable.</div><div>
We are looking for a candidate who has solid analytics engineering experience or a strong background in backend development focused on data.</div><div><b><br>
Must-Have Skills</b></div><ul><li><div><b><br>
2+ years of experience specifically in Analytics Engineering or Data Engineering</b>.</div></li><li><div><b>
Solid Python proficiency:</b> You write modular, object-oriented code, utilize relevant libraries for testing, and understand exception handling and logging.</div></li><li><div><b>
Strong skills in SQL &amp; dbt:</b> You can build scalable data models (Jinja templating, macros, incremental strategies) and understand query execution plans.</div></li><li><div><b>
Software Engineering Fundamentals:</b> Hands-on experience with <b>Git flows, CI/CD pipelines (e.g., GitHub Actions, GitLab CI)</b>, and <b>Containerization (Docker)</b>.</div></li><li><div><b>
AWS Cloud Native Experience:</b> Experience building and maintaining data workflows using serverless architectures such <b>AWS Lambda, StepFunctions, Glue, and Athena</b>.</div></li><li><div><b>
Testing Mindset:</b> Experience implementing <b>Unit Tests and Integration Tests</b> for data pipelines rather than relying solely on manual checks.</div></li><li><p><b>
Data Warehouse Ops:</b> Solid understanding of warehousing architecture (Snowflake, Redshift, or BigQuery), including partitioning and clustering concepts.</p></li></ul></div></div><div><h2 class="jobSectionHeader"><b><br>
Nice to Have
</b></h2><div><ul><li><div>Experience with <b>Infrastructure as Code (Terraform)</b> to manage cloud resources.</div></li><li><div>
Experience with orchestration tools like <b>Airflow, Dagster, or Prefect</b>.</div></li><li><div>
Knowledge of big data processing frameworks (Spark/PySpark).</div></li><li><div>
Experience with agentic coding CLI or IDE tools for more efficient planning, architecting and implementation of features.</div></li><li><div>
Familiarity with dashboarding tools (Streamlit, Preset, Tableau, etc.) &ndash; <i>Note: This is helpful for debugging and monitoring, but not the core function of the role</i>.</div></li><li><p>
B.S. or M.S. in Computer Science, Engineering, Mathematics or other relevant fields.</p></li></ul></div></div><div><h2 class="jobSectionHeader"><b>
Why us?
</b></h2><div><div>On top of a competitive package&hellip;</div><ul><li><div><br>
We are open to flexible work models: we work in a hybrid mode and remotely from anywhere in the world up to 3 months per year.</div></li><li><div>
To encourage education and professional growth, we offer an individual yearly budget of 1.200&euro;.</div></li><li><div>
You are entitled to 30 vacation days per year.</div></li><li><div>
We offer Urban Sports Club membership, company pension scheme.</div></li><li><div>
Regular team events and company events organised by our People team (Trust us, they know how to throw a party!).</div></li><li><p>
We equip you with the latest hardware and provide you with all the tools you need to thrive.</p></li></ul></div></div><div><h2 class="jobSectionHeader"><b>
Salary Range (Annual On-Target Earnings)</b></h2><div>
60,000 - 75,000 euros</div></div><div><h2 class="jobSectionHeader"><b>
Recruiting Process</b></h2><div><div>
For technical roles (Data, Engineering, and Product), candidates are encouraged to upload any technical certifications referenced in their CV via the &quot;Other Documents&quot; section of the application form.<br>
Alternatively, certification documents may be submitted after the first technical interview. Any certifications listed on the CV must be provided and successfully validated before proceeding to the second technical interview stage.</div><ul><li><div><b><br>
Step 1:</b> Value-based interview (30 mins).</div></li><li><div><b>
Step 2:</b> Deep-dive technical interview (1.5 hours) with the Data team.</div></li><li><div><b>
Step 3:</b> Practical data-crunching challenge.</div></li><li><p><b>
Step 4:</b> Team Meet &amp; Greet &mdash; the final step to ensure we're a great fit for each other.</p></li></ul></div></div><div><h2 class="jobSectionHeader"><b>
Work model</b></h2><div>
Hybrid</div></div><div><h2 class="jobSectionHeader"><b>
Desired start date</b></h2><div>
As soon as possible</div></div></div>
<br><div><h2 class="jobSectionHeader"><b>About us</b></h2><div><p>
Adsquare is the global audience &amp; location intelligence company making marketing a whole lot smarter.<br>
<br>
With eight offices around the world we are a truly international company but one united team working towards our vision: empowering companies to accelerate business growth by staying at the forefront of data-driven marketing.</p>
We are pioneers in advertising and data. We were born mobile, before it was a necessity, and have pioneered data-driven advertising in display and now DOOH. We have the smartest people, working with the best tech, so we can drive the pace of change.<br>
<br>
We are visionaries. We see a better way for marketers and are doing everything we can to make that a reality. We believe in innovation and the power of technology. We believe in constantly improving what we&rsquo;re doing because the work is never done.<br>
<br>
We believe in what we do and rise to meet our own high standards. If there&rsquo;s a problem, we fix it, humbly and without fuss or delay. Although our technology is best-of-breed, we are unassuming and modest in our approach.<br>
<br>
We are passionately candid, both with each other and with our clients. We take the time to explain our approach to their problem, confident there is nothing to hide.<br>
<br>
We are consistent and true to our word. We don&rsquo;t take shortcuts but focus on being our clients&rsquo; most reliable partner. We make promises - and we keep them. As a result, clients enjoy spending time with us, because we are good people.</div></div>

Data Analytics Engineer (m/f/d)

Control Risks

<div><p>As Senior AI Engineer you will own the AI and data layer of the platform. You will design and implement the knowledge graph architecture, build agentic pipelines that enrich entity data through AI web research, and develop the graph interrogation layer that translates natural language compliance questions into structured graph queries.</p><p>
You will work closely with the CTO and a small AI team including a data engineer and a junior AI engineer. You will have significant technical autonomy and direct influence over how the product evolves.</p><p></p><p><b>
Please submit yoru CV in English.</b></p><b><br>
Requirements</b><br>
<br>
What You&rsquo;ll Work On<p><b>
Knowledge graph architecture and implementation</b></p><ul><li>Own and evolve the platform&rsquo;s knowledge graph data model &mdash; entities (Company, Person, Community, Episodic), relationships, and temporal attributes</li><li>Implement and extend custom entity and relationship extraction pipelines using LMs, with structured output validation and confidence scoring</li><li>Use Graphiti (Zep AI&rsquo;s temporal knowledge graph framework) as the memory layer, managing episode ingestion, entity resolution, and graph updates</li><li>Design and enforce graph schema standards, ensuring consistency across data sources and ingestion pipelines</li><li>Build evaluation frameworks to measure extraction quality, entity disambiguation accuracy, and graph coverage</li></ul><p></p><p><b>
Agentic AI pipelines</b></p><ul><li>Design and implement multi-step agentic workflows that orchestrate LLM calls, web search, database lookups, and graph writes</li><li>Integrate AI web search (Tavily, Perplexity, or similar) as a tool within agentic pipelines for real-time entity enrichment</li><li>Build retrieval-augmented generation (RAG) pipelines over the knowledge graph, translating compliance queries into Cypher and natural language answers</li><li>Implement the graph interrogation layer &mdash; a conversational interface for compliance analysts to query the knowledge graph without writing Cypher</li><li>Manage LLM API integrations (Anthropic Claude, Gemini) including prompt engineering, structured outputs, and cost/latency optimisation</li></ul><p></p><p><b>
Data pipelines and integrations</b></p><ul><li>Build and maintain Python-based data ingestion pipelines reading from Databricks, connecting to external APIs (sanctions lists, corporate registries, Polixis, Vantage), and writing to Neo4j</li><li>Implement NER (named entity recognition) and entity disambiguation logic for extracting structured facts from unstructured compliance documents</li><li>Develop topic modelling pipelines to classify extracted facts as knowledge graph relationship attributes</li><li>Integrate with the .NET backend via well-defined HTTP contracts, ensuring the AI layer is independently deployable and testable</li></ul><p></p><p><b>
Research and technical leadership</b></p><ul><li>Stay current with the fast-moving agentic AI and knowledge graph literature &mdash; evaluate new frameworks, models, and techniques for production applicability</li><li>Contribute to architectural decisions with evidence: benchmarks, prototypes, and documented trade-offs</li><li>Maintain Claude Code context files (CLAUDE.md, SKILLS.md) for the AI codebase, enabling AI-augmented development across the team</li><li>Write clear technical documentation in Notion covering design decisions, data models, and operational runbooks.</li></ul><p></p>
What We&rsquo;re Looking For<p><b>
Must-have</b></p><ul><li>3+ years of professional experience in AI/ML engineering, with at least 1 year working on knowledge graphs or graph-based data systems in production</li><li>Hands-on experience with Neo4j &mdash; data modelling, Cypher query writing, schema design, and performance tuning</li><li>Deep familiarity with LLM APIs (OpenAI, Anthropic, or Gemini) &mdash; prompt engineering, structured outputs, function/tool calling, and cost management</li><li>Understanding the trade-offs between LLMs and smaller fine-tuned models (Hugging Face Transformers, sentence-transformers) &mdash; knowing when a purpose-built model outperforms a prompted general one on cost, latency, and accuracy</li><li>Experience building agentic pipelines &mdash; multi-step LLM workflows with tool use, memory, and state management</li><li>Python proficiency &mdash; you write clean, testable Python and understand async patterns for I/O-bound AI workloads</li><li>Experience with RAG architectures &mdash; vector search, hybrid retrieval, and integrating retrieval into LLM-powered applications</li><li>Ability to read and apply AI research papers &mdash; you can take a paper on narrative extraction or entity disambiguation and turn it into a working prototype</li><li>Strong English communication skills &mdash; written and verbal</li></ul><p></p><p><b>
Strong advantage</b></p><ul><li>Direct experience or knowledge with Graphiti (Zep AI) or other temporal knowledge graph frameworks</li><li>Familiarity with entity resolution and disambiguation techniques at scale</li><li>Experience with NER pipelines, topic modelling, or information extraction from compliance or financial documents</li><li>Knowledge of the third-party risk, sanctions screening, or KYC/AML domain</li><li>Experience with Databricks, Delta Lake, or similar data lakehouse platforms</li><li>Exposure to GCP (Vertex AI, Cloud Run, Pub/Sub, Cloud Storage)</li><li>Experience designing evaluation frameworks for LLM-generated structured outputs</li><li>Prior work in a RegTech, FinTech, or compliance-adjacent environment</li></ul><p></p>
What Good Looks Like in This Role<p><b>
We are direct about what we expect. The person who thrives here will:</b></p><ul><li>Treat the knowledge graph data model as the product&rsquo;s most important artefact &mdash; they think carefully about schema decisions and document them</li><li>Read the literature. When evaluating a new approach to entity disambiguation or graph memory, they check what&rsquo;s been published, not just what&rsquo;s on GitHub</li><li>Write evaluation harnesses before scaling pipelines. They know that a pipeline that produces plausible-looking output is not the same as one that produces correct output</li><li>Communicate blockers and trade-offs early. Technical uncertainty is expected &mdash; silence is not</li></ul></div>

Senior AI Engineer

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