Key Skills & Requirements:

• Core Technical
• Strong Python proficiency — you'll refactor research code into robust, tested production pipelines daily
• Awareness of performance and optimisation — profiling, memory management, and computational efficiency when scaling research code across large universes
• Solid software engineering practices: version control, unit testing, code review, CI/CD, and refactoring — you care about code quality, not just code that works
• Comfortable on Linux platforms with working knowledge of shell scripting
• Experience with data analysis libraries (NumPy, SciPy, pandas) and handling large datasets
• Familiarity with databases and data infrastructure (SQL, data pipelines, or tools like ArcticDB)
• Exposure to ML/DL frameworks (PyTorch, TensorFlow, scikit-learn) or LLM-related tooling
• Research & Domain
• Relevant mathematical knowledge — statistics, optimisation, or factor modeling — enough to understand the research you're productionising
• A keen interest in financial markets and how quantitative strategies are built and deployed
• Nice-to-Haves
• Prior internship in quantitative development, systematic investing, or front-office technology
• Education
• Currently enrolled at a top-tier university in Computer Science, Software Engineering, Mathematics, Physics, or a related field with strong computational content

We are hiring Data Site Reliability Engineers (Data SREs) to join our Global Data Engineering organization. This is an operations-focused role, responsible for ensuring the reliability, correctness, and availability of Optiver’s most critical data pipelines and platforms, many of which directly support trading and research workflows. You will be part of a globally distributed team, operating and monitoring data systems across regions.

In practice, this role combines deep technical ownership with operational responsibility. Data SREs work closely with data engineers, platform teams, and trading-facing stakeholders to ensure production data systems meet strict reliability, freshness, and correctness expectations. Beyond keeping systems running, they help evolve how we operate data platforms at scale by improving automation, observability, and operational standards across the firm. The systems supported by Data SREs include large-scale batch and streaming data pipelines, data quality and freshness monitoring, and globally operated platforms supported by follow-the-sun operational models. These systems are often on the critical path for trading and research, where data delays or inaccuracies can have immediate business impact.

What you'll do:

• Configure, launch, and maintain robust data pipelines (ETL/ELT) for ingesting and transforming datasets critical to research and trading
• Own the end-to-end reliability of critical production data pipelines, from ingestion through downstream consumption
• Ensure data quality and consistency through validation, monitoring, and robust engineering practices
• Act as the first point of contact for data incidents, investigating failures, data quality issues, and pipeline regressions, and driving them through to resolution
• Participate in incident response, root cause analysis, and post-incident reviews, with a focus on preventing recurrence
• Manage daily releases, backfills, and ad-hoc data runs, with a strong focus on safety, traceability, and environment segregation
• Design and improve monitoring, alerting, data quality checks, and operational runbooks, ensuring issues are detected early and alerts are actionable
• Build automation and tooling to reduce manual operational work and enable the platform to scale safely
• Partner closely with data engineering, platform, and trading-facing teams to ensure data systems are reliable, well-understood, and fit for purpose

Who you are:

• Experience operating or supporting production data systems, such as data pipelines, ingestion frameworks, or analytical platforms
• Strong proficiency in Python, with experience using libraries like Pandas, Arrow, and Spark
• Solid understanding of data modeling, normalization, and API development in support of large-scale analytical or trading systems
• Experience working with lakehouse architectures (e.g., Delta Lake, Databricks, AWS) to manage large-scale, high-quality analytical datasets is preferred
• An operations mindset with a strong sense of ownership, reliability, and continuous improvement
• Ability to operate with a high degree of autonomy, making sound engineering and operational decisions for production systems
• Strong communication skills and the ability to work effectively across teams and time zones
• Experience with external data ingestion is a plus
• Exposure to PCAP-based data workflows or market data capture pipelines is a plus
• Willingness to contribute to setting best practices and mentoring engineers on operational excellence and production reliability

What you'll get:

You’ll join a culture of collaboration and excellence, where you’ll be surrounded by curious thinkers and creative problem solvers. Driven by a passion for continuous improvement, you’ll thrive in a supportive, high-performing environment alongside talented colleagues, working collectively to tackle some of the most complex problems in the financial markets.

In return for your expertise, you will have access to a range of Optiver perks, including:

• A performance-based bonus structure unmatched anywhere in the industry. We combine our profits across desks, teams and offices into a global profit pool, fostering a truly collaborative environment
• The chance to work alongside diverse and intelligent peers in a rewarding environment
• Training, mentorship and personal development opportunities
• Daily breakfast, lunch and snacks
• Gym membership, sports and leisure activities, plus weekly in-house chair massages
• Regular social events, clubs and Friday afternoon drinks

Diversity statement

Optiver is committed to diversity and inclusion. We encourage applications from candidates of all backgrounds, and welcome requests for reasonable adjustments during the process.

Privacy disclaimer

Optiver 重视个人信息的保护。请您在提供个人信息给我们之前，认真阅读Optiver China Privacy Notice, 了解我们如何收集及处理您的个人信息。

Personal information protection is of utmost importance to Optiver. Before you provide any personal information to us, we strongly urge you to read our Privacy Policy to acknowledge how we collect and process your personal information.

ABOUT US

Capco is a global technology and management consultancy specializing in driving digital transformation in the financial services and insurance industries. Capco is committed to providing clients with practical solutions. We offer a globally integrated service with offices in leading financial centers across the globe. We have the people, the vision, and the passion.

We are growing through a significant growth journey, now is a very good time to join us as we expand geographically, increase headcount and disrupt the consulting market across APAC with entrepreneurial and agile thinking.

We are:

• Experts in banking and payments, capital markets and wealth and asset management
• Deep knowledge in financial services offering, including e.g. Finance, Risk and Compliance, Financial Crime, Core Banking etc.
• Committed to growing our business and hiring the best talent to help us get there
• Focus on maintaining our nimble, agile and entrepreneurial culture

ROLE RESPONSIBILITIES

We are currently seeking Senior Data Consultants to support and drive the growth of our Data practice, particularly in our Python Development stream. This is an exciting opportunity to be a leader, in a growing team of data practitioners, where you will be initiating and implementing cutting-edge data & analytics programmes for top-tier Financial Services clients.

As a Senior Data Consultant, you will be involved in developing the HK Data Practice capabilities and the broader Global Data Practice to supporting topics such as Cloud, Artificial Intelligence and Machine Learning.

KEY RESPONSIBILITIES 

SKILLS & EXPERTISE

• 5 years of experience in python development within Financial Services. 
• Advanced proficiency in Python for data processing and analytics, including libraries such as pandas, NumPy, and related frameworks.
• Strong understanding of data warehousing concepts, data modelling principles, and data governance standards.
• Solid experience working within SDLC and Agile delivery environments as a strong individual contributor.
• Experience with FIS tools, including Prophet and PMCS (configuration, runs, outputs, integration
• CI/CD: automate tests/quality checks in pipelines (e.g., GitHub Actions/GitLab/Jenkins)
• Immediately available highly preferred 

WHY JOIN CAPCO?

You will work on engaging projects with some of the largest banks in the world, on projects that will transform the financial services industry.