Principal Engineer, Data Quality Platform

Unchain Data; Greater London; Hybrid; GBP 120,000 - 180,000; Full time

Benefits offered by this job

Retirement plan contributions

Unlimited Vacation + PTO bonus

Yearly discretionary cash bonus

Employee stock options plan

Medical, dental, and vision insurance

Paid parental leave for 20 weeks

Global offsites and team outings

One-time remote-home office stipend

Wellness credit monthly

Lunch credit for in-office days

Donation matching up to $100 USD

Job summary

Talos is seeking a Principal Engineer, Data Quality Platform, to own data correctness across our platform and lead the data quality engineering team. You’ll run BAU data operations, manage reference and security master data, and own the pipelines that deliver accurate data to clients.

You’ll work in a small, independent team that collaborates with product engineering, challenging assumptions, and applying adaptive detection, LLM tooling, and robust testing across REST, WebSocket, and streaming

Qualifications

• A track record of leading data QA or data quality teams, preferably on market data or other high-throughput, real-time data.
• A deep understanding of streaming and API behaviour: throughput, WebSocket semantics, ordering, recovery and failure modes.
• Experience inventorying and testing a large API and data surface end to end.
• Hands‑on experience with data governance: cataloging, lineage, ownership.
• Experience with performance and load testing of distributed systems.
• A strong engineering background; you design platforms, not scripts, and build on shared infra.
• Practical experience applying LLM and agentic tooling to engineering problems.
• Our stack: Flink, Doris, Dagster and Spark, plus OpenMetadata (or similar).

Responsibilities

• Lead AI-first data quality engineering.
• Validate client-facing endpoints; REST, WebSocket, and cloud data delivery.
• Ensure consistency between streaming and REST views; reconcile sources of truth.
• Test resilience, load, and failure modes; design end-to-end tests.
• Drive data governance; build catalogs and lineage for APIs.
• Lead security master and reference data efforts; manage updates and rollbacks.
• Expand data quality coverage to trade signals and analytics over time.

Skills

Leading data QA teams

Data quality across high-throughput/实时

Streaming and API behavior

Test data governance tooling

LLM/agentic tooling in engineering

Performance and load testing

Independent product engineering/QA

End-to-end API/data surface testing

Tools

OpenMetadata

Flink

Doris

Dagster

Spark

Job description

Institutional Fabric for the Digital Asset Market

Founded in 2018, Talos provides institutional-grade trading technology for the global digital asset market, powering many of the major players in the crypto ecosystem. Our mission is clear: to advance the mass adoption of digital assets by seamlessly connecting institutions to the digital asset ecosystem. We are committed to building the most innovative and trusted platform in the world, supporting the entire trading lifecycle.

At Talos, you’ll find an environment that champions kindness and respect, values diverse perspectives, and upholds inclusivity at every turn. We believe every member of our team brings invaluable insights and abilities that drive Talos forward. In our pursuit of excellence, we foster a culture of trust, integrity, collaboration, and mutual growth.

We are a tight-knit yet globally distributed team of highly experienced engineers and business leaders, with hubs in New York, London, Singapore, and Cyprus. You’ll be part of a hybrid-friendly environment where your unique talents and insights will play a crucial role in building something extraordinary.

Principal Engineer, Data Quality Platform

You’ll own data correctness across Talos. You’ll lead the data quality engineering team, run BAU data operations, and own reference and security master data, along with the pipelines and platform that deliver it.

Our goal: the data we return to clients is always correct, and we find defects before a client does.

You’ll join a small team with the mandate to work independently from product engineering and challenge it. Engineering teams make assumptions about how their systems behave. Your job is to test those assumptions and prove or disprove them with evidence.

Responsibilities

• Lead AI-first data quality engineering

• Validate every client-facing endpoint continuously. The focus is our REST and WebSocket APIs. Cloud delivery (S3, Snowflake, Databricks) is also in scope. Assert correctness against independent sources of truth, across every environment and client entitlement.

• Cover streaming as well as request/response. For WebSocket, that means:

• sequencing and gap detection

• snapshot-to-increment consistency

• reconnect and replay correctness

• staleness of live subscriptions

• agreement between the streamed view and the REST view of the same state

• Use adaptive detection, not static thresholds. Learn baselines per endpoint and per market, and let them adjust as "normal" changes. Hand-set limits get noisy, go stale, and teach people to ignore alerts.

• Apply LLM and agentic tooling to generate checks from API specs and schemas, keep them current as the product changes, and triage alerts before a human sees them. Know when a deterministic rule, invariant or cross-source reconciliation is the better tool.

• Test resilience and load. Design load, performance and failure-mode tests.

• When you find a fault, raise it with the owning team with enough evidence for them to act. Drive it to resolution, then add a check that would have caught it earlier.

• Measure and publish endpoint and field coverage, time to detect, detected-before-client rate and false-positive rate.

• Run data governance

• Build and maintain a catalog of our data assets and APIs, covering lineage and downstream consumers. Maintain an understanding of assets, how they're used and what breaks when they change.

• Own data governance tooling such as OpenMetadata.

• Own reference and security master data

• Lead the build‑out of the next‑generation security master platform, then run it day to day: new listings, symbol mapping across venues, and increment and contract specs.

• Design processes for safe updates to security entries, with validation and rollback.

• Expand coverage across the firm

• Over time, extend data quality coverage beyond client APIs to:

• trade signals

• pre‑trade analytics

• client post‑trade analysis

• PMS analytics

Qualifications

• A track record of leading data QA or data quality teams, preferably on market data or other high-throughput, real-time data.

• A deep understanding of streaming and API behaviour: throughput, WebSocket semantics, ordering, recovery and failure modes.

• Experience inventorying and testing a large API and data surface end to end.

• Hands‑on experience with data governance: cataloging, lineage, ownership.

• Experience with performance and load testing of distributed systems.

• A strong engineering background. You design platforms, not scripts on a cron job, and you build on shared infrastructure rather than creating one‑off tooling.

• Practical experience applying LLM and agentic tooling to engineering problems.

• Our stack: Flink, Doris, Dagster and Spark, plus OpenMetadata (or an equivalent such as Apache Atlas). Experience with comparable tools is just as relevant.

Check out these videos and links to learn more about Talos and our culture!

• Spotlight Article: Talos Snapshot by DRW

• Podcast: 2023 episode with co‑founders Anton & Ethan

• Website: Explore Talos: Products, Investors, Team & More

• Case Studies: Real world examples of client solutions

• Awards: Talos Wins Hedgeweek Global Digital Assets Award 2024

• Culture: Award‑winning, Forbes‑listed, low‑attrition team

Andreessen Horowitz re: Talos: "The company best suited to drive institutional adoption is one that understands traditional capital markets deeply and is forward‑thinking enough to fully grasp the promise of crypto. Talos is that company."

Benefits

You will also enjoy a comprehensive array of competitive benefits, regardless of your location, within our warm, welcoming, and ambitious company culture. Some of our benefits include:

• Retirement plan contributions

• Unlimited Vacation + a PTO bonus: Employees that take 15 days of vacation, with 5 days being consecutive, receive a $2000 USD bonus.

• Yearly discretionary cash bonus

• Employee stock options plan

• Medical, dental, and vision insurance

• Paid parental leave for 20 weeks, after 1 year of service

• Global offsites and team outings

• A one‑time stipend towards at‑home office set‑up for all employees

• A wellness credit of $50 accrued monthly, to go towards things like gym memberships, ski‑passes, and work out classes.

• A lunch credit of $25 USD towards lunches for days in‑office

• Donation matching up to $100 USD annually

• Other in‑office perks: Catered lunches on Tuesdays, snacks, and drinks

Talos is proud to be an Equal Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. Talos is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [e-mail].

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