Calibration Engineer Trainee

Our opportunity
Senior Data & Analytics Engineer – Capital Modelling
Zurich is enhancing its data platform to support capital modelling, risk analytics, and finance reporting.

As a
Senior Data & Analytics Engineer
in the Capital and Risk Development team, you will design, build and maintain robust data pipelines, data models and reporting layers that provide trusted information to actuarial, risk, investment management and finance teams. You will enable reliable investor and regulatory reporting, support business steering through reliable KPIs, and develop analytics and reporting solutions that enhance efficiency within and across departments. This position requires strong data engineering and analytics skills, an interest in developing business understanding, and the ability to collaborate with cross-functional teams to deliver and improve end-to-end data flows.

Your role
As
Senior Data & Analytics Engineer
, your main responsibilities will involve:

• Collaborate with actuarial, risk, investment management, and finance colleagues to understand business needs and deliver practical solutions.
• Design and maintain data models and structures for capital, risk and market data.
• Build and operate data pipelines from source systems into our cloud data platform.
• Create analysis‑ready, business‑friendly datasets and semantic models for reporting and dashboards.
• Implement and maintain calculation logic for key capital and risk metrics.
• Contribute to data quality controls, reconciliations and documentation.
• Work with modern engineering practices (version control, code review, CI, structured environments) to enable safe and rapid change.
• Support continuous improvement of the data platform and share knowledge within the team.

Your Skills And Experience
As
Senior Data & Analytics Engineer
, your skills and experience will ideally include:

• Degree in Computer Science, Engineering, Mathematics, Statistics, Information Systems or a related field.
• Several years (typically 7+) in data engineering, analytics engineering or similar full-time or part-time roles.
• Strong SQL skills and experience with data modelling for analytics/reporting.
• Hands‑on experience with cloud data platforms (Azure, Databricks, Data Factory, Data Lake, or similar).
• Experience building and maintaining ETL/ELT pipelines.
• Good programming skills in Python, R, or similar languages.
• Proficient English, clear communication skills and a collaborative mindset; comfortable working with both technical and business stakeholders.
• Solution-oriented, with a positive attitude toward change.

Nice to Have:

• Experience with BI / reporting tools (e.g. Power BI, Tableau)
• Experience in financial services, capital modelling, risk or regulatory reporting is helpful
• We also welcome candidates with strong motivation and aptitude to quickly learn and grow in these domains.

Additional information:

• Place of work: Bratislava, Slovak Republic
• Contract type: Full-time
• Form: Hybrid - minimum 60% of time in the office

We offer
Compensation for roles at Zurich depends on a wide array of factors including but not limited to the specific role, skill set, level of experience, and subject to applicable law. Zurich thus provides a range of compensation aligned to internal job architecture and market benchmarks to ensure fair and consistent pay for comparable roles.

The starting base salary range for this position is 3 800 EUR / Gross.
Working Time Benefits
Personal days off, Concentrated work week, Additional vacation, Home office, Extra days off at occasion of childbirth, Sabbatical leave, Workcation

Monetary Benefits
Life insurance from Zurich Austria, Compensation for salary loss during sick leave, 3rd pension pillar contribution, Risk Life Insurance, Meal contribution on top of the legally required minimum, Years of service bonus, Wedding bonus, Baby bonus

Other Benefits
Edenred electronic cafeteria, Public Transport contribution, Maternity leave benefits, Massages in the office

Learning/Development
Professional Certifications, Online Education Portals, Extensive Onboarding program, Strengths based culture (GALLUP)

About Us
At Zurich Insurance, we recognize the importance of fostering an open-minded, safe and inclusive environment for everyone. We stand with diversity and respect different backgrounds and lifestyles. That's why we've implemented numerous initiatives to ensure our employees feel comfortable, accepted and respected at all times.

DeepIntent is leading the healthcare advertising industry with data-driven solutions built for the future. From day one, our mission has been to improve patient outcomes through the artful use of advertising, data science, and real-world clinical data. For more information visit, www.DeepIntent.com.

What You'll Do
DeepIntent is seeking an MLOps Engineer to join our European Data Infrastructure team. The MLOps Engineer will partner with our Data Science and AI teams to build and scale a high-performance machine learning and AI platform spanning our on-prem data centers and GPU resources - built on Python, Spark, Kubernetes, Docker, and modern orchestration frameworks (Argo Workflows, Airflow).

• Partner with Data Science and AI Engineering teams to adopt MLOps best practices and migrate training/inference workloads onto the platform
• Implement and maintain model tracking, versioning and experiment management (MLflow) with observability into model performance and drift
• Build CI/CD pipelines purpose-built for ML/AI artifacts (model registries, container image pipelines, automated retraining triggers)
• Continuously improve platform reliability, cost-efficiency and maintainability of the underlying codebase
• Establish monitoring and observability for ML/AI systems (Prometheus, Grafana) covering GPU utilization, model latency, throughput and custom ML metrics
• Design and operate ML/AI deployment infrastructure, including GPU cluster architecture, model serving and tool selection across training and inference workloads
• Build and maintain infrastructure for LLM and generative AI workloads, including model fine-tuning pipelines, vector databases, RAG architectures and inference optimization
• Collaborate with business units and Product on ML/AI-driven feature development
• Manage individual project priorities, deadlines and deliverables in a timely manner

Who You Are

• Bachelor's degree in Computer Science or similar technical field of study, or equivalent practical experience
• Strong software engineering skills in complex, distributed, multi-language systems (Python preferred)
• Hands-on experience with Spark, Docker and Kubernetes in production environments
• Experience building and operating end-to-end distributed systems
• Experience developing and maintaining ML systems built with open-source MLOps tools (e.g., MLflow, Argo, Metaflow, Airflow, Kubeflow)
• Strong understanding of software testing, benchmarking, and CI/CD practices
• Solid understanding of Linux systems administration
• Familiarity with LLM/generative AI tooling and concepts (model serving frameworks, embeddings, vector stores, RAG pipelines) is a strong plus
• Familiarity with GPU infrastructure - CUDA fundamentals, GPU scheduling/orchestration in Kubernetes, and driver/toolkit management (NVIDIA drivers, CUDA toolkit, cuDNN)
• Ability to work closely with data scientists and understand their tooling and workflows (Jupyter, notebooks, experiment tracking)
• An enthusiastic learner with a genuine thirst for keeping up with the fast-moving ML/AI infrastructure landscape

We believe great work starts with great support. That’s why DeepIntent offers a competitive, holistic benefits package designed to empower you both professionally and personally.

Here’s what you can expect when you join our team based in the US: Competitive base salary plus performance based bonus or commission, comprehensive medical, dental, and vision insurance, 401K match program, flexible PTO policy and paid holidays, remote friendly culture with flexible work options, career development and advanced education support, WFH and internet stipends, plus many more perks and benefits!

Here’s what you can expect when you join our team based in India: Competitive base salary plus performance based bonus, comprehensive medical insurance, and paid holidays. Hybrid-friendly culture with flexible work options, professional development reimbursement, WiFi reimbursement and health and wellness allowance plus many more perks and benefits!

Here's what you can expect when you join our team based in Europe: Competitive base salary plus performance-based bonus, comprehensive medical insurance, and flexible PTO. Hybrid-friendly culture with flexible work options, professional development reimbursement, WiFi reimbursement, and parental leave plus many more perks and benefits!

DeepIntent is committed to bringing together individuals from different backgrounds and perspectives. We strive to create an inclusive environment where everyone can thrive, feel a sense of belonging, and do great work together. DeepIntent is an Equal Opportunity Employer, providing equal employment and advancement opportunities to all individuals. We recruit, hire and promote into all job levels the most qualified applicants without regard to race, color, creed, national origin, religion, sex (including pregnancy, childbirth and related medical conditions), parental status, age, disability, genetic information, citizenship status, veteran status, gender identity or expression, transgender status, sexual orientation, marital, family or partnership status, political affiliation or activities, military service, immigration status, or any other status protected under applicable federal, state and local laws. If you have a disability or special need that requires accommodation, please let us know in advance. DeepIntent’s commitment to providing equal employment opportunities extends to all aspects of employment, including job assignment, compensation, discipline and access to benefits and training.

CCPA Notice: If you are a California resident applying for a role at DeepIntent, we may collect personal information as part of the application process in accordance with the California Consumer Privacy Act (CCPA). To learn more about the categories of information we collect and your rights, please contact PeopleOps@deepintent.com to see our full Applicant Privacy Notice.

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.

Your role
As a
Data Engineer (Fivetran HVR)
, you will be at the heart of our enterprise data integration capability - designing and delivering reliable, high-performance replication and pipeline solutions that connect critical business systems across on-premises and cloud environments. You'll play a key role in enabling data modernisation, cloud migration, and real-time analytics for our clients.

Your tasks
In this role you will play a key role in:

• Designing, developing, and maintaining robust data integration and replication solutions using Fivetran HVR, including Change Data Capture (CDC)-based pipelines across hybrid and cloud environments
• Optimising replication performance, including throughput, latency, and data availability, while proactively monitoring and resolving pipeline failures and data quality issues
• Collaborating closely with Data Architects, DBAs, Cloud Engineers, Application Teams, and Business Analysts to deliver end-to-end data integration solutions
• Supporting enterprise cloud data platform initiatives, including migrations to Azure Data Lake and Databricks, as part of broader data modernisation programmes
• Performing root cause analysis on data integration incidents and implementing long-term corrective actions to ensure production stability
• Developing automation and data processing scripts using Python and SQL to enhance pipeline efficiency and reduce manual intervention
• Contributing to DataOps practices, CI/CD processes, and data quality frameworks to drive engineering excellence across the delivery lifecycle

Your profile
We're looking for someone who combines deep technical expertise in data integration with a collaborative mindset and a passion for solving complex data challenges at scale.

• 4+ years of experience in Data Engineering, Data Integration, ETL/ELT Development, or Data Platform Engineering, with hands-on expertise in Fivetran HVR administration, configuration, and troubleshooting
• Strong understanding of Change Data Capture (CDC), enterprise replication patterns, and experience working with large-scale relational databases including SQL Server, PostgreSQL, and/or SAP HANA
• Proficiency in advanced SQL and Python scripting, with experience building and supporting cloud-based data platforms on Azure, Databricks, or equivalent modern data environments
• Experience supporting enterprise-scale production data environments, with the ability to take ownership of incidents, communicate clearly with stakeholders, and drive issues through to resolution with a focus on reliability and data quality

Preferred:

• Familiarity with DataOps, CI/CD, and infrastructure automation practices
• Experience with data modelling, data warehousing, and dimensional design
• Familiarity with SAP source systems and enterprise application integrations
• Experience working in Agile delivery environments

What You'll Love About Working Here

• Well-being culture: medical care with Medicover, private life insurance, and sports card. But we went one step further by creating our own Capgemini Helpline offering therapeutical support if needed and the educational podcast 'Let's talk about wellbeing' which you can listen to on Spotify.
• Access to over 70 training tracks with certification opportunities (e.g., GenAI, Architects, Google) on our NEXT platform. Dive into a world of knowledge with free access to Education First languages platform, TED Talks and Udemy Business materials and trainings.
• Continuous feedback and ongoing performance discussions thanks to our performance management tool GetSuccess supported by a transparent performance management policy.
• Enjoy hybrid working model that fits your life - after completing onboarding, connect work from a modern office with ergonomic work from home, thanks to home office package (including laptop, monitor, and chair). Ask your recruiter about the details.

Get to know us
Capgemini is committed to diversity and inclusion, ensuring fairness in all employment practices. We evaluate individuals based on qualifications and performance, not personal characteristics, striving to create a workplace where everyone can succeed and feel valued.

Do you want to get to know us better? Check our Instagram — @capgeminipl or visit our Facebook profile — Capgemini Polska. You can also find us on YouTube.

About Capgemini
Capgemini is the business transformation partner for enterprises in the age of AI. We help organizations imagine and build an intelligent, sustainable future, combining AI, technology and human ingenuity to transform how they operate, innovate and grow. With unique end-to-end capabilities spanning strategy, technology, engineering and intelligent operations, we bring together deep industry expertise and market-leading capabilities in AI, cloud and data to turn ambition into measurable business outcomes at scale. Supported by a robust ecosystem of partners and nearly 60 years of expertise, Capgemini is a responsible and diverse global organization of over 410,000 team members in more than 50 countries. The Group reported 2025 revenues of €22.5 billion.

Make it real | www.capgemini.com

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer (Cloud) based in Switzerland.
This role offers the opportunity to modernize data infrastructure and build scalable cloud-based data products in a globally distributed technology environment.

You will lead the migration of data workloads from legacy SQL Server environments to modern cloud platforms.

Your work will directly improve the reliability, quality, performance, and accessibility of analytical data.

You will design production-grade ETL/ELT pipelines, analytical models, and cloud data workflows using modern engineering practices.

The role combines hands-on data engineering with cloud infrastructure, platform automation, and AI-assisted engineering initiatives.

You will collaborate with analysts, engineers, and business stakeholders to translate complex requirements and legacy logic into robust solutions.

This is an excellent opportunity for a senior engineer who enjoys solving challenging data problems and shaping modern cloud platforms.

Accountabilities

• Migrate data products, analytical workloads, and associated processes from MS SQL Server to a modern cloud data platform.
• Analyze legacy SQL, ETL workflows, data models, and business logic, redesigning them to align with the target cloud architecture.
• Build, maintain, and optimize scalable batch data pipelines and analytical data models for production use.
• Deploy, configure, and operate managed cloud data services, including data warehouses, workflow orchestration, managed compute, and storage.
• Validate migrated data, investigate discrepancies, and implement measures to maintain high standards of data accuracy and quality.
• Collaborate with data analysts and business stakeholders to clarify requirements, understand business logic, and ensure technical solutions support analytical needs.
• Contribute to data platform reliability, performance optimization, cost efficiency, monitoring, and broader engineering best practices.
• Develop and improve AI-assisted engineering automation for data engineering workflows, including reusable agent capabilities, shared specifications, evaluation frameworks, quality controls, and supporting tools.
• Apply automation and infrastructure engineering practices to improve the efficiency, consistency, and scalability of data workflows.
• Identify technical risks and opportunities for continuous improvement across data pipelines, cloud infrastructure, and analytical workloads.

Requirements

• Strong professional background in Data Engineering with advanced SQL skills and extensive experience working with relational databases.
• Hands-on experience with GCP data technologies or another major cloud platform, with strong practical knowledge of services such as BigQuery, Cloud Composer, and Google Cloud Storage.
• Proven experience designing and operating production-grade ETL/ELT pipelines and analytical data models.
• Experience deploying, configuring, and managing cloud data services, including workflow orchestration, managed or serverless compute, analytical warehouses, and cloud storage.
• Strong Python skills or proficiency in another general-purpose programming language, with practical application across data engineering, platform automation, and analytical workloads.
• Solid understanding of cloud infrastructure concepts, including IAM, networking, monitoring, CI/CD, and infrastructure configuration.
• Experience working with legacy data warehouses, complex SQL environments, and business logic that requires careful analysis and modernization.
• Ability to investigate data issues, identify root causes, validate migrations, and maintain strong data quality standards.
• Strong problem-solving and analytical capabilities, combined with a structured and engineering-focused approach to complex technical challenges.
• Comfortable collaborating with technical and non-technical stakeholders in a distributed, international environment.
• Fluent Russian communication skills.

Benefits

• Fully remote, full-time opportunity with the flexibility to work from anywhere.
• Initial compensation or salary range shared with candidates during the recruitment process before employment begins.
• 28 calendar days of vacation per year.
• 7 wellness days annually for personal, household, or recovery needs.
• Referral bonuses of up to $5,000 for successful candidate recommendations.
• 50% reimbursement for professional training, international conferences, and industry events.
• Corporate discounts for English-language lessons.
• Health support, including reimbursement of up to $1,000 gross per year per employee for eligible employees who do not have access to corporate medical insurance, usable toward health insurance or eligible medical expenses for the employee and close relatives.
• Workplace support, including equipment and workspace resources where available, or reimbursement of up to $1,000 gross every three years toward coworking or home-office costs in other locations.
• Internal gamified recognition program where colleagues can award bonuses that can be exchanged for merchandise, team-building activities, massage certificates, and other benefits.
• Opportunity to work with modern cloud data technologies, AI-assisted engineering automation, and globally distributed technical teams.

How Jobgether Works
We use an
AI-powered matching process
to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice:
By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.