At a Glance
- Tasks: Lead a dynamic data team and shape the future of our data strategy.
- Company: Join Alpaca, a global leader in innovative financial services technology.
- Benefits: Enjoy competitive salary, stock options, health benefits, and a home-office setup stipend.
- Other info: Work remotely with a diverse team across the globe.
- Why this job: Make a significant impact in a fast-growing company with cutting-edge technology.
- Qualifications: 8+ years in data engineering, with strong leadership and technical skills.
The predicted salary is between 63000 - 77000 £ per year.
Who We Are
Alpaca is a US-headquartered, global leader in agent-first brokerage infrastructure for stocks, ETFs, options, crypto, fixed income, 24/5 trading, and more.
Amongst our subsidiaries, Alpaca is a licensed financial services company, serving hundreds of financial institutions across 40 countries with our institutional-grade APIs.
This includes broker-dealers, investment advisors, wealth managers, hedge funds, and crypto exchanges, totalling over 10 million brokerage accounts.
Our global team is a diverse group of experienced engineers, traders, and brokerage professionals who are working to achieve our mission of opening financial services to everyone on the planet.
We're deeply committed to open-source contributions and fostering a vibrant community, continuously enhancing our award-winning, developer-friendly API and the robust infrastructure behind it.
Alpaca is proudly backed by $400 million in funding from top-tier global investors including Portage Ventures, Spark Capital, Tribe Capital, Social Leverage, Horizons Ventures, Opera Tech Ventures, SBI Group, Derayah Financial, Unbound, Peak XV, Elefund, and Y Combinator.
Our Team Members
We're a dynamic team of 400+ globally distributed members who thrive working from our favorite places around the world, with teammates spanning the USA, Canada, Japan, Hungary, Nigeria, Brazil, the UK, and beyond!
We're searching for passionate individuals eager to contribute to Alpaca's rapid growth.
If you align with our core values—Stay Curious, Have Empathy, and Be Accountable—and are ready to make a significant impact, we encourage you to apply.
Your Role
We are looking for a Head of Data to lead Alpaca’s ~15-person data department across Platform Engineering, Analytics Engineering, and Data Science.
You will own the data strategy, the team’s execution, and the department’s roadmap.
The Data department serves every function at
Alpaca: it powers partner invoicing and revenue attribution, provides the analytical foundation for sales, product, and compliance, and operates the data platform that processes hundreds of millions of events daily.
You will manage three team leads, balancing operational delivery (invoicing, embedded analytics, regulatory reporting) with strategic bets (self-service warehouse, AI-powered analytics, enterprise search).
This is a player-coach role.
You will set direction for the team while staying close enough to the technical details to make architecture decisions, unblock your leads, and represent data’s capabilities to the executive team.
Things You Get To Do
- Lead and develop three sub-teams: Platform Engineering & ETL, Analytics Engineering, and Data Science & Analytics. Manage leads, set priorities, and ensure delivery.
- Own the Data Lakehouse architecture: Trino, Iceberg/GCS, Airflow, Airbyte, Redpanda CDC, dbt. Make build-vs-buy decisions on tooling.
- Drive partner invoicing accuracy and evolution: ensure invoicing logic is versioned, reproducible, and scales with new pricing mechanisms and product launches.
- Deliver embedded analytics: expose warehouse data to partners via Broker Dash, SSR pipelines, and API-based reporting. Own row-level security and entitlements.
- Support product launches with data change management: coordinate data impact analysis for new products (fixed income, global stocks, perps, 24/5 trading) across downstream datasets, dashboards, and reverse ETL.
- Accelerate self-service: move the organization toward self-serve analytics via semantic layers, data catalogues, and conversational BI so the data team can shift from ad-hoc queries to strategic projects.
- Guide AI/ML enablement: oversee enterprise AI search, agent-based workflow automation, and LLM-powered analytics. Help balance vendor solutions with in-house development.
- Collaborate with Finance, Sales, Product, Compliance, and Customer Success to translate business needs into data products.
- Manage infrastructure costs: keep data + cloud cost ratio under target as AUC grows.
- Operate production systems: own on-call processes, incident response, and SLOs for data freshness, accuracy, and availability.
Who You Are (Must-Haves)
- 8+ years in data engineering or analytics, including 3+ years managing data teams (leads + ICs).
- Deep experience with modern data stack: dbt, Trino/Presto or equivalent query engines, Apache Iceberg or similar table formats, cloud object storage.
- Hands-on experience with ETL/ELT patterns at scale: CDC (Debezium/Kafka), batch (Airflow/dbt), streaming, and reverse ETL.
- Track record of building self-service analytics capabilities for non-technical stakeholders.
- Experience with financial data: trading, invoicing, revenue attribution, or regulatory reporting in fintech or financial services.
- Proficiency in Python and SQL. Comfortable reading code, reviewing PRs, and making architecture decisions.
- Experience managing distributed/remote teams across multiple time zones.
- Strong stakeholder management: you can translate between executive priorities and engineering execution.
- Experience with GCP (GKE, GCS, Big Query migration), Kubernetes, Helm, Terraform.
Who You Might Be (Nice-to-Haves)
- Experience with brokerage or broker-dealer operations (clearing, settlement, market making, reconciliation).
- Familiarity with LLM/AI tooling: MCP, vector databases, enterprise search, conversational BI (Wren AI, Cube).
- Background in compliance analytics (AML/Actimize, KYC, margin calls).
- Exposure to open-source data catalogues (Open Metadata, Collate) and data quality frameworks.
How We Take Care of You
- Competitive Salary & Stock Options
- Health Benefits
- New Hire Home-Office Setup: One-time USD $500
- Monthly Stipend: USD $150 per month via a Brex Card
Alpaca is proud to be an equal opportunity workplace dedicated to pursuing and hiring a diverse workforce.
Recruitment Privacy Policy
Director of Data Platform employer: Alpaca
Alpaca is an exceptional employer that fosters a collaborative and innovative work culture, particularly for the Acquisition Engineering Lead role based in the UK. Employees benefit from competitive salaries, comprehensive health benefits, and support for home-office setups, all while having ample opportunities for professional growth and development within a dynamic team focused on enhancing user experiences.
StudySmarter Expert Advice🤫
We think this is how you could land Director of Data Platform
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Alpaca!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Director of Data Platform at Alpaca.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Alpaca.
✨Apply Directly through Our Website
When you find a suitable opening like Director of Data Platform at Alpaca, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Director of Data Platform
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Alpaca, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Alpaca. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Alpaca
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Alpaca!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
