Principal Data Engineer

Every major business function, including Finance, People, Procurement, Tax, and Compliance, operates on its own version of the truth: fragmented, siloed, and manually managed. You'll build the governed data foundation that replaces this, greenfield, on a modern stack, with real architectural ownership and production delivery in your hands.

The Problem You're Solving

One truth across multiple domains. Multiple business functions. Multiple definitions of the same metrics. Your role is designing and building the unified semantic layer that brings this together. This is a real modelling challenge where getting the business logic right matters as much as getting the code right.

Governance that's engineered, not bolted on. Lineage, access control, column masking, PII classification, and data stewardship are designed into every domain from day one using Unity Catalog and DataHub. The goal is a governance model rigorous enough to hold up to regulatory scrutiny and trusted enough that business teams stop building their own extracts.

The data layer that AI depends on. Optiver is building conversational analytics and AI agents that query business data through a semantic layer. What Databricks Genie surfaces to the business depends entirely on what you build underneath it.

What you’ll do

• Architect and own delivery of shared data products across Finance, People, Procurement, and Compliance, from design decisions through to production
• Build and evolve the semantic layer that powers reporting, self-service analytics, conversational analytics, and Databricks Genie, writing the models, tests, and documentation that make it trustworthy
• Design and build scalable data pipelines, data models, and governed data products using Databricks, dbt, SQL, and PySpark
• Implement governance capabilities end-to-end, including Unity Catalog access controls, column-level security, data classification, lineage, and data quality standards
• Drive DataHub adoption by defining metadata standards, lineage definitions, and data ownership models that make discoverability a first-class engineering concern
• Translate complex and ambiguous requirements from senior stakeholders into production-grade data solutions, owning the problem from conversation to deployed model
• Set the engineering standard for the team through the quality of your code, architecture decisions, and pull request reviews
• Partner with the broader data team to continuously improve CI/CD, testing frameworks, observability, and data quality practices

Who you are

• 12+ years of experience designing and building production data solutions, with a track record of leading complex technical initiatives end-to-end.
• Track record of architectural ownership and designing end-to-end data solutions
• Expert-level SQL and data transformation skills, with strong hands-on experience in dbt, PySpark, or both. You design data products for scale, write tests without friction, and have clear opinions on where each tool's limits are
• Deep experience with Databricks, Lakehouse architectures, or comparable modern data technologies, including Delta table design, Unity Catalog governance, compute trade-offs, and downstream BI or AI workloads
• Experience implementing governance at scale, including access control, PII handling, column-level security, data lineage, and data quality management in production environments
• Experience building trusted business-facing data products within Finance, People/HR, Procurement, Operations, or similar domains. You understand business logic well enough to challenge unclear or incorrect requirements

Why This Is Challenging

You’ll join a team building the foundations of how Optiver understands and operates its business. The data products you build will be used by business teams, leadership, and increasingly by AI-powered tools and conversational analytics experiences.

You’ll work across a broad range of domains, from People and Finance to Procurement and Compliance, gaining exposure to how a global trading firm operates while building solutions on a modern stack that includes Databricks, dbt, Unity Catalog, DataHub, and Databricks Genie.

No prior trading or financial experience is needed - our onboarding program will kick-start your career at Optiver and support you in gaining all the relevant knowledge about our business.

Who we are

At Optiver, our mission is to constantly improve the market by injecting liquidity, providing accurate pricing, increasing transparency and acting as a stabilizing force no matter the market conditions. With a focus on continuous improvement, we participate in the safeguarding of healthy and efficient markets for everyone who participates. As one of the largest market making institutions, we are a trusted partner of 70+ exchanges across the globe.

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. Motivated by a passion for continuous improvement, you’ll thrive in a supportive, high-performing environment alongside talented colleagues, working collectively to tackle the toughest problems in the financial markets.

In addition, you’ll receive:

• A performance-based bonus structure, enabling all of our employees to benefit from our global profit pool.
• The opportunity to work alongside best-in-class professionals from over 50 different countries.
• 25 paid vacation days in your first year, increasing to 30 from your second year onwards.
• Training opportunities, discounts on health insurance, and fully paid first-class commuting expenses.
• Extensive office perks, including breakfast, lunch and dinner, world-class barista coffee, in-house physio and chair massages, organized sports and leisure activities, and Friday afternoon drinks.
• Training and continuous learning opportunities, including access to conferences and tech events.

Please note:

• We do not require any assistance from third-parties including agencies in the recruitment of this role

Diversity statement Optiver is committed to diversity and inclusion.

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