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(senior) devops engineer - platform services (m/w/d) Jobs in Berlin

dev ops engineer

Bundesdruckerei-Gruppe

<div>Wir suchen zum n&auml;chstm&ouml;glichen Zeitpunkt eine engagierte Pers&ouml;nlichkeit f&uuml;r den Bereich DevOps Engineering mit dem Schwerpunkt Aufbau und Betrieb einer Elastic-basierten Observability Platform.
Du erf&uuml;llst nicht alle Voraussetzungen? Kein Problem &ndash; wir m&ouml;chten dich trotzdem kennenlernen!
Ihr Aufgabenbereich
<ul><li>Konzeption, Aufbau und Betrieb von Elastic-Clustern</li><li>
Implementierung und Wartung von Elastic SIEM</li><li>
Realisierung von Funktionserweiterungen und ma&szlig;geschneiderten L&ouml;sungen auf Basis der Projektanforderungen innerhalb des Logging-&Ouml;kosystems</li><li>
Entwicklung von Anwendungen zur automatisierten Einbindung externer Datenquellen in Elasticsearch, einschlie&szlig;lich der Bereitstellung von Kibana-Spaces und der rollenbasierten Zugriffskontrolle</li><li>
Deployment-Automatisierung mit Ansible, Terraform, Helm, Kustomize, ArgoCD oder GitLab CI/CD</li><li>
Qualit&auml;tssicherung der Plattform durch Mitwirkung an Testautomatisierungen in Zusammenarbeit mit dem Quality Team</li><li>
Anbindung von Authentifizierungsdiensten (LDAP, SAML2, OIDC, Keycloak)</li></ul>
Ihr Profil
<ul><li>Erfolgreich abgeschlossenes Studium der Informatik oder eines vergleichbaren Studiengangs bzw. IT-technische Berufsausbildung mit praktischer Erfahrung im beschriebenen Aufgabengebiet</li><li>
Erfahrungen mit dem Elastic Stack auf dem Niveau &bdquo;Elasticsearch Engineer II&ldquo;</li><li>
Erfahrungen in der &Uuml;berwachung und Telemetrieerfassung sowie in der Ausarbeitung von SLIs</li><li>
Kenntnisse in allgemeiner Programmierung, Skripting und Infrastructure as Code (z. B. Go, Shell, Ansible, Terraform)</li><li>
Allgemeines IT-Know-how, insbesondere im Betrieb von Softwarel&ouml;sungen bei externen Cloud-Anbietern sowie im Umgang mit agilen Methoden (Scrum, Kanban)</li><li>
Systematische, zielorientierte und selbstst&auml;ndige Arbeitsweise</li><li>
Sehr gute Deutschkenntnisse in Wort und Schrift (mindestens Niveau C1)</li></ul></div>

DevOps Engineer – Elastic & Observability (m/w/d)

Thales

<div>Location: Berlin, Germany
We Say HI*
DevOps Engineer (w/m/d)
Thales ist ein weltweit f&uuml;hrender Anbieter von Spitzentechnologien f&uuml;r die Bereiche Verteidigung, Luft- und Raumfahrt sowie Cyber Security und Digital Identity.
Deutsche Unternehmen und die &ouml;ffentlichen Verwaltungen hierzulande sind bereit, ihre digitale Transformation und den Einsatz von KI zu beschleunigen &ndash; aber sie werden niemals Kompromisse bei der Sicherheit ihrer sensibelsten Daten eingehen. Genau hier setzen wir als Thales Deutschland in Partnerschaft mit Google Cloud und unserem neuen, in Gr&uuml;ndung befindlichen Unternehmen an. Mit einer neuen, zu 100 % deutschen Unternehmenseinheit geben wir eine konkrete Antwort auf die strengen Anforderungen des BSI. Was wir hier schaffen, ist eine lokal und vollst&auml;ndig autonom betriebene &sbquo;Trusted Cloud&lsquo;. Sie erm&ouml;glicht den Zugriff auf das breiteste Service-Portfolio am Markt, w&auml;hrend alles strikt unter europ&auml;ischer Gerichtsbarkeit bleibt. Durch die Zusammenf&uuml;hrung deutscher und franz&ouml;sischer Standards wie SecNumCloud, C5 und C3-A bieten wir unseren Kunden eine beispiellose Resilienz und Business Continuity. Dies ist ein Wendepunkt f&uuml;r unsere Branche und ein entscheidender Schritt hin zu einem starken, souver&auml;nen digitalen Europa.
Ihre Mission als DevOps / Site Reliability Engineer:<ul><li>
Betrieb und Weiterentwicklung hochverf&uuml;gbarer souver&auml;ner GCP-Services mit Fokus auf Stabilit&auml;t, Skalierbarkeit und Performance</li><li>
&Uuml;berwachung von SLI/SLO-Kennzahlen sowie Analyse und Behebung von Produktionsst&ouml;rungen im 24x7-Betrieb inklusive Teilnahme an einer Rufbereitschaft</li><li>
Zusammenarbeit mit globalen SRE- und GCP-Expertenteams zur schnellen Incident-Analyse, Fehlerbehebung und nachhaltigen Service-Optimierung</li><li>
Dokumentation von Betriebswissen, Standardisierung von Prozessen sowie Weiterentwicklung von Automatisierungs- und Operational-Playbooks</li><li>
Durchf&uuml;hrung von Post-Mortem-Analysen nach Incidents zur Identifikation von Verbesserungspotenzialen und F&ouml;rderung einer kontinuierlichen Optimierung der Systemlandschaft</li></ul>
Darauf freuen wir uns:<ul><li>
Erfolgreich abgeschlossenes Studium der Informatik, Ingenieurwissenschaften oder ein vergleichbarer Masterabschluss</li><li>
Mehrj&auml;hrige Erfahrung im Bereich DevOps / Site Reliability Engineering (SRE) sowie in der Automatisierung von Betriebs- und Incident-Management-Prozessen</li><li>
Kenntnisse in regulierten Branchen mit hohen Compliance-Anforderungen, z.B. Banking, Versicherungen, Healthcare oder vergleichbaren Umfeldern mit hohen Compliance-Anforderungen</li><li>
Erfahrung in internationalen Arbeitsumgebungen sowie sehr gute Deutsch- und Englischkenntnisse in Wort und Schrift</li><li>
Erfahrungen mit Google Cloud Platform (GCP) sowie eine hohe Lernbereitschaft und Begeisterung f&uuml;r moderne Cloud-Technologien</li></ul>
Thales investiert j&auml;hrlich mehr als 4,5 Milliarden Euro in Forschung und Entwicklung in Schl&uuml;sseltechnologien wie k&uuml;nstliche Intelligenz, Cybersicherheit, Quanten- und Cloud-Technologien.
Im Jahr 2025 erwirtschaftete die Gruppe einen Umsatz von 22,1 Milliarden Euro.
F&uuml;r mehr als 85.000 Mitarbeitende in 65 L&auml;ndern er&ouml;ffnen wir zukunftsweisende Perspektiven, verwirklichen individuelle Karrierewege und erm&ouml;glichen kreative Freir&auml;ume. Dies gelingt durch Mut, Vielfalt und den festen Willen, die anspruchsvollen Herausforderungen unserer Zeit sicherer und inklusiver zu gestalten. Mit unserer nachhaltigen, werteorientierten Personalf&uuml;hrung treten wir aktiv f&uuml;r Diversit&auml;t ein.
Say HI* &ndash; Ihr Weg zu uns
Wenn die Zeichen der Zeit auf Ver&auml;nderung stehen, sind unsere internationalen Teams da, um der Komplexit&auml;t von heute mit den branchenf&uuml;hrenden Technologien von morgen zu begegnen. Sind Sie dabei? Ihr Ansprechpartner Andre Fuhrmann freut sich schon auf Ihre Online-Bewerbung.
Andre Fuhrmann &ndash; Talent Acquisition Partner
+49 7156 / 302 - 22002<ul><li>Human Intelligence</li></ul>
#LI-AF1
#LI-HYBRID</div>

DevOps Engineer

Zeta Global

<div>WHO WE ARE

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform &ndash; powered by one of the industry&rsquo;s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com. 


The Role

We&rsquo;re looking for a skilled ML Engineer / Data Scientist with 3+ years of software or applied ML experience to design, build, and improve machine learning solutions in a dynamic cloud environment, primarily on AWS.This role sits at the intersection of data science and engineering: exploring data, developing models, running rigorous experiments, and bringing the best approaches into production with a reliable, reproducible workflow. If strong Python skills, curiosity about hard modeling problems, and collaborative work in multicultural teams are a fit, this is a chance to do meaningful, end-to-end ML work&mdash;not just notebooks, and not just infrastructure. 

<div>
Who you are:
<ul>
<li>Strong foundation in machine learning, statistics and experiment design.</li>
<li>Experience building models for real business or product problems, not only academic benchmarks.</li>
<li>Comfortable working with structured and unstructured data: feature engineering, dataset construction, labeling quality, leakage checks, and train/validation/test discipline.</li>
<li>Able to compare approaches with clear metrics, error analysis, and sound judgment about tradeoffs (accuracy, latency, cost, maintainability).</li>
<li>Interest in modern ML, including classical ML, deep learning, and LLM / GenAI workflows where relevant (fine-tuning, RAG, evaluation, prompt/versioning).</li>
<li>Proficient in Python and able to write clean, modular, testable code.</li>
<li>Experience developing and deploying ML solutions in a cloud environment, especially AWS.</li>
<li>Comfortable moving from prototype to production: packaging models, building inference paths, monitoring performance, and iterating after launch.</li>
<li>Independent engineer who can own work from problem framing experimentation implementation rollout.</li>
<li>Excellent written and spoken English.</li>
<li>Enjoy working closely with engineers, product partners, and other data scientists.</li>
<li>Clear communicator who can explain methods, results, and limitations to technical and non-technical audiences.</li>
<li>Master&rsquo;s degree in Science or Engineering (Computer Science, Mathematics, Physics, Statistics, or similar), or equivalent practical experience.</li>
</ul>
Nice to have:
<ul>
<li>Experience with scikit-learn, PyTorch, TensorFlow, XGBoost, or similar modeling stacks.</li>
<li>Familiarity with ML experiment tracking and reproducibility (e.g. MLflow, W&amp;B).</li>
<li>Experience with SQL, data warehouses/lakes, and pipeline tools such as Airflow, dbt, or Spark.</li>
<li>Exposure to feature stores, embedding pipelines, or vector search for retrieval-based systems.</li>
<li>Experience building HTTP/gRPC APIs or lightweight services around model inference.</li>
<li>Working knowledge of Docker, basic orchestration, and CI/CD (e.g. GitLab CI).</li>
<li>Experience in agile, remote and async team environments.</li>
<li>Publications, patents, Kaggle/competition results, or open-source ML contributions.</li>
</ul>
What you might like about this role:
<ul>
<li>Hands-on modeling work with room to explore, benchmark, and improve real systems.</li>
<li>Collaboration on ML patent submissions and participation in weekly ML / research paper review meetings.</li>
<li>A multicultural, engineering-focused team with strong peer support.</li>
<li>High trust and autonomy&mdash;clear goals, freedom in how to reach them.</li>
<li>Internal product impact: meaningful projects that improve developer and user experience, not endless maintenance tickets.</li>
<li>Short approval cycles and solid product partnership.</li>
<li>A healthy meeting policy and emphasis on protecting focus time.</li>
<li>Flexible hours, remote/home office options, and a calm, engineers-only office when on-site.</li>
<li>Competitive compensation, including stock options.</li></ul> 
<div>
</div><div></div><div><div>We&rsquo;re hiring across multiple levels. Title, scope, and compensation depend on experience&mdash;from strong applied ML generalists to senior people who can lead modeling direction and mentor others.

We&rsquo;re especially interested in candidates who are technically strong, intellectually curious, and motivated by difficult, ambiguous problems where good data science and solid engineering both matter. 


PEOPLE &amp; CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual&rsquo;s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.
We&rsquo;re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here: https://zetaglobal.com/blog/a-look-into-zetas-ergs/

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 


#LI-NP1</div></div></div></div>

ML Ops Engineer

<div>
 
 &nbsp;
 
 
 
 WHO WE ARE&nbsp;
 
 
 
 Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform &ndash; powered by one of the industry&rsquo;s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.
 
 
 &nbsp;
 
 
 
 The Role
 
 
 
 We&rsquo;re looking for a skilled&nbsp;
 
 ML Engineer / Data Scientist
 
 &nbsp;with&nbsp;
 
 3+ years of software or applied ML experience
 
 &nbsp;to design, build, and improve machine learning solutions in a dynamic cloud environment, primarily on&nbsp;
 
 AWS
 
 .This role sits at the intersection of&nbsp;
 
 data science and engineering
 
 : exploring data, developing models, running rigorous experiments, and bringing the best approaches into production with a reliable, reproducible workflow. If strong Python skills, curiosity about hard modeling problems, and collaborative work in multicultural teams are a fit, this is a chance to do meaningful, end-to-end ML work&mdash;not just notebooks, and not just infrastructure.
 
 
 &nbsp;
 
 
 
 Who you are:
 
 
 <ul>
 <li>
 Strong foundation in&nbsp;
 
 machine learning,&nbsp;statistics
 
 and&nbsp;
 
 experiment design
 
 .
 </li>
 <li>
 Experience building models for&nbsp;
 
 real business or product problems
 
 , not only academic benchmarks.
 </li>
 <li>
 Comfortable working with&nbsp;
 
 structured and unstructured data
 
 : feature engineering, dataset construction, labeling quality, leakage checks, and train/validation/test discipline.
 </li>
 <li>
 Able to compare approaches with clear&nbsp;
 
 metrics
 
 , error analysis, and sound judgment about tradeoffs (accuracy, latency, cost, maintainability).
 </li>
 <li>
 Interest in&nbsp;
 
 modern ML
 
 , including classical ML, deep learning, and&nbsp;
 
 LLM / GenAI workflows
 
 &nbsp;where relevant (fine-tuning, RAG, evaluation, prompt/versioning).
 </li>
 <li>
 Proficient in&nbsp;
 
 Python
 
 &nbsp;and able to write&nbsp;
 
 clean, modular, testable&nbsp;code
 
 .
 </li>
 <li>
 Experience developing and deploying ML solutions in a&nbsp;
 
 cloud environment
 
 , especially&nbsp;AWS.
 </li>
 <li>
 Comfortable moving from prototype to production: packaging models, building inference paths, monitoring performance, and iterating after launch.
 </li>
 <li>
 Independent engineer who can own work from&nbsp;
 
 problem framing &rarr; experimentation &rarr; implementation &rarr; rollout
 
 .
 </li>
 <li>
 Excellent&nbsp;
 
 written and spoken English
 
 .
 </li>
 <li>
 Enjoy working closely with engineers, product partners, and other data scientists.
 </li>
 <li>
 Clear communicator who can explain methods, results, and limitations to technical and non-technical audiences.
 </li>
 <li>
 
 Master&rsquo;s degree
 
 &nbsp;in Science or Engineering (Computer Science, Mathematics, Physics, Statistics, or similar),&nbsp;
 
 or equivalent practical experience
 
 .
 </li>
 </ul>
 
 
 Nice to have:
 
 
 <ul>
 <li>
 Experience with&nbsp;
 
 scikit-learn,&nbsp;PyTorch,&nbsp;TensorFlow,&nbsp;XGBoost
 
 , or similar modeling stacks.
 </li>
 <li>
 Familiarity with&nbsp;
 
 ML experiment tracking
 
 &nbsp;and reproducibility (e.g. MLflow, W&amp;B).
 </li>
 <li>
 Experience with&nbsp;
 
 SQL
 
 , data warehouses/lakes, and pipeline tools such as&nbsp;
 
 Airflow,&nbsp;dbt, or&nbsp;Spark
 
 .
 </li>
 <li>
 Exposure to&nbsp;
 
 feature stores
 
 , embedding pipelines, or&nbsp;
 
 vector search
 
 &nbsp;for retrieval-based systems.
 </li>
 <li>
 Experience building&nbsp;
 
 HTTP/gRPC APIs
 
 &nbsp;or lightweight services around model inference.
 </li>
 <li>
 Working knowledge of&nbsp;
 
 Docker
 
 , basic orchestration, and CI/CD (e.g.&nbsp;
 
 GitLab CI
 
 ).
 </li>
 <li>
 Experience in&nbsp;
 
 agile
 
 ,&nbsp;
 
 remote
 
 and&nbsp;
 
 async
 
 &nbsp;team environments.
 </li>
 <li>
 Publications, patents, Kaggle/competition results, or open-source ML contributions.
 </li>
 </ul>
 
 
 What you might like about this role:
 
 
 <ul>
 <li>
 
 Hands-on modeling work
 
 &nbsp;with room to explore, benchmark, and improve real systems.
 </li>
 <li>
 Collaboration on&nbsp;
 
 ML patent submissions
 
 &nbsp;and participation in&nbsp;weekly ML / research paper review&nbsp;meetings.
 </li>
 <li>
 A&nbsp;
 
 multicultural, engineering-focused team
 
 &nbsp;with strong peer support.
 </li>
 <li>
 
 High trust and autonomy
 
 &mdash;clear goals, freedom in how to reach them.
 </li>
 <li>
 
 Internal product impact
 
 : meaningful projects that improve developer and user experience, not endless maintenance tickets.
 </li>
 <li>
 
 Short approval cycles
 
 &nbsp;and solid product partnership.
 </li>
 <li>
 A&nbsp;
 
 healthy meeting policy&nbsp;
 
 and emphasis on protecting focus time.
 </li>
 <li>
 
 Flexible hours
 
 , remote/home office options, and a calm, engineers-only office when on-site.
 </li>
 <li>
 
 Competitive compensation
 
 , including&nbsp;stock options.
 </li>
 </ul>
 &nbsp;
 
 We&rsquo;re hiring across
 
 multiple levels
 
 . Title, scope, and compensation depend on experience&mdash;from strong applied ML generalists to senior people who can lead modeling direction and mentor others.
 
 
 We&rsquo;re especially interested in candidates who are&nbsp;
 
 technically strong, intellectually curious, and motivated by difficult, ambiguous problems
 
 &nbsp;where good data science and solid engineering both matter.
 
 
 &nbsp;
 
 
 &nbsp;
 
 
 
 PEOPLE &amp; CULTURE AT ZETA
 
 
 
 Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual&rsquo;s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.&nbsp;&nbsp;
 
 
 We&rsquo;re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:&nbsp; https://zetaglobal.com/blog/a-look-into-zetas-ergs/&nbsp;
 
 
 
 ZETA IN THE NEWS!
 
 
 
 https://zetaglobal.com/press/?cat=press-releases&nbsp;
 
 
 &nbsp;
 
 
 
 
 
</div>

Amazon Web Services (AWS)

<div>
 
 Description
 
 
 
 AWS is set to introduce the inaugural European Sovereign Cloud (ESC), marking a significant development in Utility Computing (UC). To spearhead this initiative, we are actively seeking experienced systems engineers with a strong background in cloud operations. As part of the AWS Managed Operations team, you will play a pivotal role in building and leading operations and development teams dedicated to delivering high-availability AWS services, including EC2, S3, Dynamo, Lambda, and Bedrock, exclusively for EU customers. For more information on ESC please check out our blog: https://aws.amazon.com/blogs/aws/in-the-works-aws-european-sovereign-cloud/
 
 
 Your responsibilities will encompass overseeing the launch of the ESC in 2025, working closely with global AWS teams, and influencing the evolution of AWS services and technology. A typical day in this role involves collaborating with technology leaders, contributing to the enhancement of day-to-day operations, and ensuring improvements in availability, reliability, latency, performance, and efficiency of the ESC.
 
 
 The overarching goal is to deliver scalable services and ensure a high-availability experience for EU customers. If you are an experienced professional ready for a challenging and impactful opportunity, we invite you to join our efforts in building a best-in-class development engineering and operations team that aligns with AWS' commitment to customer satisfaction and continual innovation.
 
 
 A day in the life
 
 
 You&rsquo;ll spend a majority of your time operating and improving one of the largest software systems. Over the course of a week, you will review the operational health of the services in your team&rsquo;s care, and as soon as you figure out why there was an anomaly, you write up an actionable bug report. As a responsible engineer, you&rsquo;ve learned never to make changes to production systems without a plan, so you reviewed then executed changes following a change management process to one of the production systems in your care. Later in the week, you help to resolve your team&rsquo;s backlog of operational issues. You round off the week by writing a cool script that you shared with your team which helps get to root cause faster of a hard problem that you diagnosed earlier.
 
 
 You will be required to occasionally participate in an &ldquo;on-call&rdquo; rotations to resolve incidents occurring out-of-hours.
 
 
 Eligibility requirement
 
 
 <ul>
 <li>
 Fluency in written and spoken English is required.
 </li>
 <li>
 Candidate must be a national of an EU member state and residing in the EU to operate the AWS European Sovereign Cloud.
 </li>
 <li>
 Amazon will provide relocation support for successful applicants relocating within the European Union.
 </li>
 <li>
 Employees will participate in an On-Call rota.
 
 
 </li>
 </ul>
 
 About The Team
 
 
 
 Utility Computing (UC)
 
 
 European Sovereign Cloud (ESC) is a part of AWS Utility Computing (UC).
 
 
 AWS Utility Computing (UC) provides product innovations &mdash; from foundational services such as Amazon&rsquo;s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS&rsquo;s services and features apart in the industry. As a member of the UC organization, you&rsquo;ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS. Within AWS UC, Managed Operations engineers engage with AWS customers who require specialized security solutions for their cloud services.
 
 
 Diverse Experiences
 
 
 AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn&rsquo;t followed a traditional path, or includes alternative experiences, don&rsquo;t let it stop you from applying.
 
 
 Why AWS
 
 
 Amazon Web Services (AWS) is the world&rsquo;s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating &mdash; that&rsquo;s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
 
 
 Work/Life Balance
 
 
 We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there&rsquo;s nothing we can&rsquo;t achieve.
 
 
 Inclusive Team Culture
 
 
 AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.
 
 
 Mentorship &amp; Career Growth
 
 
 We&rsquo;re continuously raising our performance bar as we strive to become Earth&rsquo;s Best Employer. That&rsquo;s why you&rsquo;ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
 
 
 
 Basic Qualifications
 
 
 
 <ul>
 <li>
 This role requires you to be a national of an EU member state
 </li>
 <li>
 Bachelor's degree in computer science (or related IT discipline) or equivalent industry experience
 </li>
 <li>
 Knowledge or experience in scripting (Bash, Python, or Ruby) or software development (Java, TypeScript, or similar), coupled with Linux and networking fundamentals to effectively troubleshoot and optimize system performance and reliability.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Able to execute standard operating procedures and following operational best practices
 </li>
 <li>
 Knowledge or experience operating service in AWS or other cloud systems or services
 </li>
 <li>
 Knowledge or experience operating 24x7 high-availability, distributed software applications, performance tuning software applications and optimizing fleet utilization and monitoring frameworks (such as CloudWatch, Datadog, Grafana, Elastic or similar)
 </li>
 <li>
 Knowledge or experience with Infrastructure as Code, (such as CDK, CloudFormation, Puppet, Chef, Ansible, or similar)
 
 
 </li>
 </ul>
 Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
 
 
 m/w/d
 
 
 Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.
 
 
 
 
 Company
 
 - AWS European Sovereign Cloud Development Center GmbH - M94
 
 
 Job ID: A3082914
</div>

DevOPS/Systems Engineer, Managed Operations

<div><div><div><h2 class="jobSectionHeader">Ihr Aufgabenbereich</h2></div><div><ul>
<li>Verst&auml;rkung des Developer-Experience-Teams beim weiteren Ausbau der Application-Operations-Platform der Bundesdruckerei-Gruppe</li>
<li>Automatisierung von IT-Prozessen (Continuous Integration, Continuous Delivery, Testautomation) und eigenst&auml;ndige Durchf&uuml;hrung von Administrations- und Konfigurationst&auml;tigkeiten</li>
<li>Evaluierung neuer Technologien und stetige Weiterbildung im entsprechenden Bereich</li>
<li>Entwicklung von Managed Services zur Vereinfachung der Entwicklungs- und Betriebsprozesse</li>
<li>Fachliche und technologische Beratung der Product-Owner- und Software-Engineering-Teams bei Produkt- und Projektanforderungen</li>
<li>Planung und Entwicklung von Microservice-Architekturen</li>
<li>Dokumentation von Arbeitsergebnissen und Systemen in Ticketing- und Wissensplattformen</li>
</ul></div></div><div><div><h2 class="jobSectionHeader">Ihr Profil</h2></div><div><ul>
<li>Erfolgreich abgeschlossenes Studium der Informatik bzw. einer vergleichbaren Studienrichtung oder IT-technische Berufsausbildung mit einschl&auml;giger Berufserfahrung in vergleichbarer Position</li>
<li>Grundverst&auml;ndnis f&uuml;r DevOps-Prinzipien und Interesse an deren Umsetzung in der Praxis</li>
<li>Berufspraxis in der Implementierung von CI-/CD-Pipelines sowie im Deployment von gro&szlig;en Softwareanwendungen vorteilhaft</li>
<li>Expertise im Umgang mit Docker/Kubernetes; idealerweise Erfahrung mit Red Hat Openshift und Istio</li>
<li>Grundkenntnisse in Java, Microservices-Architekturen und API-Design (REST, Messaging)</li>
<li>Idealerweise Erfahrung mit Logging (Elasticsearch, Fluentd, Kibana) und Monitoring (Prometheus/Alertmanager, Grafana)</li>
<li>analytische, serviceorientierte Arbeitsweise und Freude an der Arbeit in agilen Teams (Scrum, Kanban)</li></ul></div></div></div>
 <div><div><h2 class="jobSectionHeader">Ihre Vorteile</h2>
</div><div><ul><li>Gemeinsam mehr erreichen: toller Teamspirit in einem kompetenten und zukunftssicheren Arbeitsumfeld mit einzigartigen Projekten</li>
<li>Attraktive Arbeitsbedingungen: ausgewogene Balance zwischen Beruf und Privatleben dank flexibler Arbeitsmodelle und -zeiten und 30 Tagen Urlaub im Jahr</li>
<li>Moderne Arbeitsausstattung: top Equipment, agile Entwicklungsmethoden mit modernem Tech Stack und innovativen Kollaborationstools</li>
<li>Pers&ouml;nliche Entwicklung: individuelle Weiterbildungsm&ouml;glichkeiten sowie Fach- und F&uuml;hrungskr&auml;fteprogramme</li>
<li>Optimale Verkehrsanbindung: attraktiver Standort mit sehr guter Anbindung an den &ouml;ffentlichen Nahverkehr</li>
<li>Angebote zum Gesundbleiben: Sportkooperationen, Pr&auml;ventionskurse und Laufevents</li>
<li>Weitere Extras: betriebliche Altersvorsorge, verm&ouml;genswirksame Leistungen, unterst&uuml;tzende Ma&szlig;nahmen bei der Kinderbetreuung und der Pflege von Angeh&ouml;rigen</li></ul></div></div>

DevOps Engineer (m/w/d) Platform Services

Talon.One LinkedIn Jobs

<div><div>ABOUT TALON.ONE: 


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.

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.</div> 


ABOUT THE TEAM:

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.

ABOUT THE ROLE:

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. 


ONCE YOU ARE HERE YOU WILL: 

<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>
WHAT WE NEED YOU TO BRING TO THE TABLE:
<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> 


ABOUT TECHNOLOGY:
<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> 

<div>
WHAT'S IN IT FOR YOU:</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>

Senior Data Engineer

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