Τι θα κάνεις
- Δημιουργείς CI/CD pipelines για δεδομένα και AI/ML workloads χρησιμοποιώντας Azure DevOps και Git
- Παρακολουθείς και διαχειρίζεσαι την παραγωγή δεδομένων και AI/ML υποδομών με εργαλεία όπως Grafana, Azure Monitor, ELK Stack
- Αντιμετωπίζεις περιστατικά και επιλύεις προβλήματα με ελάχιστο χρόνο διακοπής λειτουργίας
- Δημιουργείς και διαχειρίζεσαι operational runbooks, SOPs και πρωτόκολλα incident response
- Βελτιστοποιείς την απόδοση και τον προγραμματισμό χωρητικότητας των συστημάτων δεδομένων
- Παρακολουθείς και βελτιώνεις τα λειτουργικά metrics και SLAs για τις AI/ML πλατφόρμες
- Διαχειρίζεσαι κόστη cloud και Databricks μέσω πρακτικών FinOps
- Υποστηρίζεις την ανάπτυξη παραγωγής και τη διαχείριση αλλαγών
Βασικές προϋποθέσεις
- 5+ χρόνια εμπειρίας
- Γνώσεις Python, SQL και Bash scripting για αυτοματοποίηση και διαχείριση pipelines
- Εμπειρία με CI/CD εργαλεία όπως Azure DevOps και Git
- Λειτουργίες Kubernetes και Docker, και εργαλεία ορχήστρωσης όπως Apache Airflow
- Εργαλεία παρακολούθησης και observability όπως Grafana, Azure Monitor και ELK Stack
- Τεχνολογίες cloud Azure, Databricks και Azure Data Factory
- Γνώση πρακτικών SLA, incident management, change management και operational runbooks
- Πληροφορική / Μηχανική / Πληροφοριακά Συστήματα / Οποιοδήποτε Πεδίο
Παροχές
- Ανταγωνιστικός μισθός και παροχές που περιλαμβάνουν ασφάλεια ζωής/υγείας, μπόνους απόδοσης, μηνιαία κουπόνια, εταιρικό αυτοκίνητο (ανάλογα με το επίπεδο), ευέλικτες εργασιακές ρυθμίσεις, πρόγραμμα αγοράς μετοχών εργαζομένων, γονική άδεια, εταιρικές εκπτώσεις και συνεχή εκπαίδευση & ανάπτυξη μέσω παγκόσμιων πλατφορμών και τοπικής ακαδημίας.
Περιγραφή Θέσης
ARE YOU READY to step into the New Era (NewRA) of AI-driven banking?
At Accenture Newra AI Hub, we are not just building technology, we are redefining how banking operates. As part of our strategic collaboration with Piraeus, Newra is designed to responsibly embed AI at the core of its business, moving beyond experimentation to real-world impact at scale. Built to make a real difference, Newra reflects our belief that AI creates value only when it genuinely improves people’s lives.
You will work on advanced AI solutions that span the full spectrum of the bank -from core banking systems to customer experience- simplifying complexity, automating critical processes and delivering measurable results where they matter most.
Joining Newra means becoming part of a high-performing team of innovators at the beginning of a major reinvention. This is a space for people who approach AI with depth, discipline and purpose. You will collaborate across disciplines, develop future-proof skills, and help turn technology into real-world transformation.
As an AI Ops & Data Ops Senior Engineer , you’ll keep the AI and data platform fast, reliable, observable, and continuously improving. You’ll build the operational backbone for data and AI/ML workloads, automating deployments, monitoring pipelines, enforcing SLAs, improving incident response, and helping teams ship safely at speed. You’ll work where platform engineering, data operations, AI operations, and FinOps meet, making sure the systems behind AI products are resilient, measurable, and ready to scale.
What you'll build
CI/CD pipelines for data and AI/ML workloads, automated build, test, deployment, and release management using Azure DevOps and Git
Production monitoring and observability for data pipelines and AI/ML infrastructure: Grafana, Azure Monitor, ELK Stack, and logging solutions
Incident response and resolution, triage data pipeline incidents, system alerts, and operational issues with minimal downtime
Operational runbooks, SOPs, and incident response protocols to ensure repeatable, reliable operations
Performance tuning and capacity planning for data systems and infrastructure
AIOps practices: track and report on operational metrics, SLAs, and system availability for AI/ML data platforms
FinOps: monitor and optimise cloud and Databricks costs (tagging, budgets, chargeback, showback, right-sizing)
Support production deployments and change
Qualification
What we need
Degree in Computer Science, Engineering, Information Systems, or related field
~5 years in data engineering, DevOps, platform engineering, or a similar ops-focused role
Python, SQL, and Bash scripting for automation and pipeline maintenance
Hands-on with CI/CD tooling: Azure DevOps, Git — building and maintaining automated deployment pipelines
Kubernetes and Docker operations; Apache Airflow or similar orchestration tools
Observability stack experience: Grafana, Azure Monitor, ELK Stack / logging solutions
Databricks / Azure Data Factory and Azure cloud services (Storage, VMs, AKS)
Operational mindset: SLA ownership, incident management, change management, and runbook discipline
Strong analytical and problem-solving skills; proficiency in Greek and English
Nice to have:
FinOps tooling: Azure Cost Management, tagging strategies, chargeback / showback frameworks
PostgreSQL / SQL Server / NoSQL; infrastructure-as-code (Terraform, Bicep)
•SRE practices: error budgets, reliability targets, postmortem culture
What's in it for you
Competitive salary and benefits, including but not limited to: life/health insurance, performance based bonuses, monthly vouchers, company car (depending on management level), flexible work arrangements, employee share purchase plan, parental leave and various corporate discounts
Continuous training & development through global platforms & local academy. At Accenture, we believe in bringing the best to our clients through continuous learning & improvement – from basic skills to industry-specific content – available to all our people
Career coaching and mentorship to help you manage your career and develop professionally
Ongoing strength and skill-based evaluation process
Various opportunities to develop your career across a spectrum of clients, industries and projects
Diverse and inclusive culture
Opportunities to get involved in corporate citizenship initiatives, from volunteering to doing charity work
Under our Brain Regain initiative, extra relocation benefits may apply




