Impress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Target Resume Now
About the Role
You'll build the governed data foundation that replaces fragmented, siloed, and manually managed business functions on a modern stack, with architectural ownership and production delivery.
Responsibilities
- 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
Requirements
- 8+ 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.
- 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.
- Understand business logic well enough to challenge unclear or incorrect requirements
Skills
- Databricks
- dbt
- SQL
- PySpark
- Unity Catalog
- DataHub
- Databricks Genie
- Lakehouse architectures
- Delta table design
- Column-level security
- Data classification
- Data lineage
- Data quality management
- CI/CD
- Testing frameworks
- Observability
Experience Level
- 8+ years of experience
Benefits
- Performance-based bonus structure
- Global profit pool
- Training, mentorship and personal development opportunities
- Daily breakfast, lunch and an in-house barista
- Gym membership plus weekly in-house chair massages
- Regular social events, including a company trip every two years
- Guided relocation, a competitive relocation package and visa sponsorship where necessary
About the Company
- 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.
Equal Opportunity
- Optiver is committed to diversity and inclusion.
- We encourage applications from candidates of all backgrounds, and welcome requests for reasonable adjustments during the process.