Within Verisign, our Data Engineering Team is responsible for designing, building and maintaining large-scale, high-throughput (millions requests per second) data products and services delivering actionable operational and business intelligence. To help us advance our products, we are looking for a skilled Mid-Level Data Engineer.

An ideal candidate should deeply care about all steps of data lifecycle (ingestion, enhancement, storage, processing, visualization), be fluent in a JVM-based language, and be eager to learn as needed. They should have an understanding of fundamentals including core Computer Science concepts accompanied by hands-on problem-solving experience ideally involving large-scale distributed systems. Obtaining these competencies often requires an equivalent of a bachelor’s degree and 5 years of practical work experience. We are also open to other career paths.

The candidate will be involved in all aspects of data engineering, including ideation, design, implementation, deployment, customer onboarding, and support. This will often imply regular cross-team collaboration with Verisign Data Platform, Business, Infrastructure, Engineering, Security, and Operations. We expect the candidate to take full ownership of the data products, regularly interacting with the internal customers, proactively identifying, prioritizing, and delivering on their common data needs.

Key Responsibilities:

• Design, build and optimize real-time and batch data processing pipelines.
• Develop and maintain data processing components that implement transformation, normalization, and enrichment logic.
• Build and maintain interactive dashboards and visualizations for internal stakeholders.
• Develop and maintain containerized workloads deployed in Kubernetes environments using CI/CD automation.
• Ensure system and data pipelines reliability through monitoring, observability, and alerting practices.
• Troubleshoot complex issues in distributed data systems and resolve performance bottlenecks.
• Support internal customers using data products and analytical platforms.
• Contribute to continuous improvement by applying data engineering best practices, particularly in hybrid cloud environments.

Required Skills

• Strong programming fundamentals with experience in object-oriented or functional programming languages
• Experience working with data lake and analytical technologies (e.g., Iceberg, Druid, Hive, Object Storage).
• Familiarity with streaming data platforms such as Apache Kafka.
• Experience implementing CI/CD pipelines (e.g. Jenkins).
• Strong analytical, troubleshooting, and problem-solving skills.
• Ability to collaborate effectively with cross-functional stakeholders.

Preferred Skills

• Proficiency in Java or other JVM-based programming languages (e.g., Scala).
• Hands-on experience with distributed data processing frameworks such as Apache Spark or Akka Streams.
• Experience with containerization and orchestration technologies (Docker, Kubernetes) in production environments.
• Strong understanding of distributed systems concepts and performance optimization.
• Experience working in large-scale, production-grade data environments.
• Experience with delivering business insights by leveraging data visualization tools such as Grafana, Tableau or Superset.

An ideal candidate will have a blend of technical skills, an intention to grow themselves and those around them, and allow Verisign to continuously improve the delivery of business and operational insights:

Qualifications:

• Bachelor’s degree in computer science or a related technical field, or equivalent combination of education and experience
• Prior experience developing and managing production-grade data pipelines
• Achieving this skill-set typically requires a minimum of 5 years of relevant industry experience in addition to a Bachelors or Masters degree, but we are open to alternative career paths

Who is Artefact?

Artefact is a next-generation strategy and data consulting firm dedicated to transforming organizations through data and AI. We combine the rigor of top-tier strategy consulting with deep expertise in data, digital, and analytics to help clients achieve tangible business impact.

With 1,800+ consultants, data scientists, and engineers across 23 countries, we work with global leaders such as Samsung, L’Oréal, Orange, and Sanofi. Our Romandie office (Geneva/Lausanne) is at the heart of Artefact’s growth, advising clients on their most pressing strategic challenges — from AI strategy and governance to digital transformation roadmaps and new business model design.

Main Responsibilities

As a Senior AI & Data Engineer, you will be the architect of the "AI Factory." Your role is less about training models from scratch and more about building the industrial-grade pipelines, infrastructure, and security frameworks required to run AI in a highly regulated environment.

• Production-Grade AI Infrastructure: Design and implement robust MLOps and LLMOps pipelines specifically for banking environments, focusing on data residency, air-gapping possibilities, and high availability.

• Data Engineering for AI: Build scalable ETL/ELT pipelines to feed RAG (Retrieval-Augmented Generation) systems, ensuring data lineage, quality, and strict access control (RBAC).

• DevOps & Automation: Own the CI/CD lifecycle for AI assets. Automate the deployment of model APIs, vector databases, and monitoring stacks using Infrastructure as Code (IaC).

• Hybrid Cloud & On-Prem: Navigate complex hybrid-cloud architectures (Azure/AWS/GCP vs. Private Cloud) common in Swiss banking.

• Technical Advisory: Act as a bridge between IT Infrastructure, Risk/Compliance, and Business units to translate AI potential into stable, governed reality.

Candidate Profile

Engineer first, consultant second — with a builder’s mindset and a track record of shipping.

• Experience: 4+ years in Data Engineering, DevOps, or Software Engineering, with at least 2 years focused on deploying Machine Learning or AI systems at scale.

• The "DevOps" Stack: Expert knowledge of Docker, Kubernetes (K8s), and CI/CD tools (GitHub Actions, GitLab CI, or Jenkins). Experience with Terraform or Pulumi is a strong plus.

• The "Data" Stack: Advanced SQL and Python. Deep experience with data orchestration (Airflow, Dagster), streaming (Kafka), and modern data warehouses (Snowflake, Databricks).

• AI/LLM Implementation: Hands-on experience with the "plumbing" of AI: Vector databases (Milvus, Qdrant, or pgvector), model serving (BentoML, vLLM), and RAG orchestration (LangChain/LlamaIndex).

• Banking Domain: Solid understanding of financial data structures and the regulatory landscape (Model Risk Management, Audit trails, Data anonymization).

• Languages: English is mandatory. German (B2 or higher) is a significant advantage for the Zurich market and stakeholder management.

• Education: Master’s degree in Computer Science, Software Engineering, or a related quantitative field.

Nice to have

• Experience with responsible AI/governance frameworks, security reviews, and cost optimization.

• Domain experience in finance.

• Contributions to open-source, publications, or conference talks.

Why Join Us

• Strategy with a Data Edge: Operate at the intersection of boardroom strategy and cutting-edge AI engineering.

• Zurich Office Impact: High visibility from day one; help shape our Swiss footprint and work directly with senior leadership.

• Learning & Growth: Advanced training across strategy, AI/ML/LLM, and cloud; international missions and communities of practice.

• Culture of Doers: Innovation, action, collaboration. We move fast, deliver impact, and support each other’s growth.

Location: Zurich

If you don’t meet 100% of the criteria, we still want to hear from you. Passion, curiosity, and impact orientation matter — tell us about yours.

Who is Artefact?

Artefact is a next-generation strategy and data consulting firm dedicated to transforming organizations through data and AI. We combine the rigor of top-tier strategy consulting with deep expertise in data, digital, and analytics to help clients achieve tangible business impact.

With 1,800+ consultants, data scientists, and engineers across 23 countries, we work with global leaders such as Samsung, L’Oréal, Orange, and Sanofi. Our Romandie office (Geneva/Lausanne) is at the heart of Artefact’s growth, advising clients on their most pressing strategic challenges — from AI strategy and governance to digital transformation roadmaps and new business model design.

Main Responsibilities

As a Senior AI & Data Engineer, you will be the architect of the "AI Factory." Your role is less about training models from scratch and more about building the industrial-grade pipelines, infrastructure, and security frameworks required to run AI in a highly regulated environment.

• Production-Grade AI Infrastructure: Design and implement robust MLOps and LLMOps pipelines specifically for banking environments, focusing on data residency, air-gapping possibilities, and high availability.

• Data Engineering for AI: Build scalable ETL/ELT pipelines to feed RAG (Retrieval-Augmented Generation) systems, ensuring data lineage, quality, and strict access control (RBAC).

• DevOps & Automation: Own the CI/CD lifecycle for AI assets. Automate the deployment of model APIs, vector databases, and monitoring stacks using Infrastructure as Code (IaC).

• Hybrid Cloud & On-Prem: Navigate complex hybrid-cloud architectures (Azure/AWS/GCP vs. Private Cloud) common in Swiss banking.

• Technical Advisory: Act as a bridge between IT Infrastructure, Risk/Compliance, and Business units to translate AI potential into stable, governed reality.

Candidate Profile

Engineer first, consultant second — with a builder’s mindset and a track record of shipping.

• Experience: 4+ years in Data Engineering, DevOps, or Software Engineering, with at least 2 years focused on deploying Machine Learning or AI systems at scale.

• The "DevOps" Stack: Expert knowledge of Docker, Kubernetes (K8s), and CI/CD tools (GitHub Actions, GitLab CI, or Jenkins). Experience with Terraform or Pulumi is a strong plus.

• The "Data" Stack: Advanced SQL and Python. Deep experience with data orchestration (Airflow, Dagster), streaming (Kafka), and modern data warehouses (Snowflake, Databricks).

• AI/LLM Implementation: Hands-on experience with the "plumbing" of AI: Vector databases (Milvus, Qdrant, or pgvector), model serving (BentoML, vLLM), and RAG orchestration (LangChain/LlamaIndex).

• Banking Domain: Solid understanding of financial data structures and the regulatory landscape (Model Risk Management, Audit trails, Data anonymization).

• Languages: English is mandatory. German (B2 or higher) is a significant advantage for the Zurich market and stakeholder management.

• Education: Master’s degree in Computer Science, Software Engineering, or a related quantitative field.

Nice to have

• Experience with responsible AI/governance frameworks, security reviews, and cost optimization.

• Domain experience in finance.

• Contributions to open-source, publications, or conference talks.

Why Join Us

• Strategy with a Data Edge: Operate at the intersection of boardroom strategy and cutting-edge AI engineering.

• Zurich Office Impact: High visibility from day one; help shape our Swiss footprint and work directly with senior leadership.

• Learning & Growth: Advanced training across strategy, AI/ML/LLM, and cloud; international missions and communities of practice.

• Culture of Doers: Innovation, action, collaboration. We move fast, deliver impact, and support each other’s growth.

Location: Zurich

If you don’t meet 100% of the criteria, we still want to hear from you. Passion, curiosity, and impact orientation matter — tell us about yours.

Who is Artefact?

Artefact is a next-generation strategy and data consulting firm dedicated to transforming organizations through data and AI. We combine the rigor of top-tier strategy consulting with deep expertise in data, digital, and analytics to help clients achieve tangible business impact.

With 1,800+ consultants, data scientists, and engineers across 23 countries, we work with global leaders such as Samsung, L’Oréal, Orange, and Sanofi. Our Romandie office (Geneva/Lausanne) is at the heart of Artefact’s growth, advising clients on their most pressing strategic challenges — from AI strategy and governance to digital transformation roadmaps and new business model design.

Main Responsibilities

As a Senior AI & Data Engineer, you will be the architect of the "AI Factory." Your role is less about training models from scratch and more about building the industrial-grade pipelines, infrastructure, and security frameworks required to run AI in a highly regulated environment.

• Production-Grade AI Infrastructure: Design and implement robust MLOps and LLMOps pipelines specifically for banking environments, focusing on data residency, air-gapping possibilities, and high availability.

• Data Engineering for AI: Build scalable ETL/ELT pipelines to feed RAG (Retrieval-Augmented Generation) systems, ensuring data lineage, quality, and strict access control (RBAC).

• DevOps & Automation: Own the CI/CD lifecycle for AI assets. Automate the deployment of model APIs, vector databases, and monitoring stacks using Infrastructure as Code (IaC).

• Hybrid Cloud & On-Prem: Navigate complex hybrid-cloud architectures (Azure/AWS/GCP vs. Private Cloud) common in Swiss banking.

• Technical Advisory: Act as a bridge between IT Infrastructure, Risk/Compliance, and Business units to translate AI potential into stable, governed reality.

Candidate Profile

Engineer first, consultant second — with a builder’s mindset and a track record of shipping.

• Experience: 4+ years in Data Engineering, DevOps, or Software Engineering, with at least 2 years focused on deploying Machine Learning or AI systems at scale.

• The "DevOps" Stack: Expert knowledge of Docker, Kubernetes (K8s), and CI/CD tools (GitHub Actions, GitLab CI, or Jenkins). Experience with Terraform or Pulumi is a strong plus.

• The "Data" Stack: Advanced SQL and Python. Deep experience with data orchestration (Airflow, Dagster), streaming (Kafka), and modern data warehouses (Snowflake, Databricks).

• AI/LLM Implementation: Hands-on experience with the "plumbing" of AI: Vector databases (Milvus, Qdrant, or pgvector), model serving (BentoML, vLLM), and RAG orchestration (LangChain/LlamaIndex).

• Banking Domain: Solid understanding of financial data structures and the regulatory landscape (Model Risk Management, Audit trails, Data anonymization).

• Languages: English is mandatory. German (B2 or higher) is a significant advantage for the Zurich market and stakeholder management.

• Education: Master’s degree in Computer Science, Software Engineering, or a related quantitative field.

Nice to have

• Experience with responsible AI/governance frameworks, security reviews, and cost optimization.

• Domain experience in finance.

• Contributions to open-source, publications, or conference talks.

Why Join Us

• Strategy with a Data Edge: Operate at the intersection of boardroom strategy and cutting-edge AI engineering.

• Zurich Office Impact: High visibility from day one; help shape our Swiss footprint and work directly with senior leadership.

• Learning & Growth: Advanced training across strategy, AI/ML/LLM, and cloud; international missions and communities of practice.

• Culture of Doers: Innovation, action, collaboration. We move fast, deliver impact, and support each other’s growth.

Location: Zurich

If you don’t meet 100% of the criteria, we still want to hear from you. Passion, curiosity, and impact orientation matter — tell us about yours.

IMC has a strong presence in traditional Finance and has been expanding into Crypto over the last years. Through its overseas affiliates, IMC provides liquidity and trades on many cryptocurrency exchanges and DeFi protocols. You can expect a dynamic, fast-paced environment that delivers a steady stream of challenges and opportunities, with one of the most exciting aspects of the job being our quick feedback loop in the research, development and deployment of strategies.

As a Data Engineer, you‘ll be joining our core engineering team. You will contribute to our proprietary low-latency trading system, acquire market and trading data, implement ETL processes and collaborate with traders and researchers on improving the trading results.

Your Core Responsibilities:

• Collaborate on developing market and trading data pipeline systems, both in batch mode and streaming mode.
• Extend data pipelines to multiple exchanges/platforms and across different areas of application.
• Work closely together with other engineers and researchers, providing efficient data solutions for our research and trading operations.

Your Skills and Experience:

• Masters in Computer Science, Mathematics, Physics or a related technical field. Industry experience in big data would be a big plus.
• Skills in data pipeline technologies such as Clickhouse, Flink and Kafka. Experience with Kubernetes is a plus.
• Proficient programming experience in Java/Scala & Python, C++ being a plus.
• You are absolutely fluent in English and enjoy working in an international team.
• You are eager to design, develop, test, deploy, maintain and improve software.

Location and Office Culture:

• IMC office in Zug, Switzerland
• Note that this is an onsite role, with some but limited flexibility for working from home
• You can expect a dynamic, fast-paced environment that delivers a steady stream of challenges and opportunities
• One of the most exciting aspects of the job is our quick feedback loop in the research, development and deployment of strategies
• We give people lots of responsibility and the support they need to make an impact from day one
• We promise you a flat structure and an open, collaborative culture that stimulates the sharing of ideas, knowledge and technology between our teams and offices