Data Platform Engineering Manager

Favia; United Kingdom; Remote; GBP 120,000 - 170,000; Full time

Job summary

Favia is seeking a senior data platform lead to head the streaming and data platform layer, designing systems to move, transform, and serve data in real time across trading, analytics, and product systems.

You will own the architecture for high-volume data stacks using Spark, Kafka, Iceberg, RisingWave, and Apache Flink, and drive AI-powered automation and self-healing infrastructure while mentoring a team of senior engineers.

Qualifications

• 8+ years in data engineering, platform engineering, or distributed systems.
• Experience leading engineering teams (3+ years).
• Strong cloud data lake experience with AWS offerings.

Responsibilities

• Lead and grow a team of senior data platform engineers building real-time streaming infrastructure.
• Own architecture and roadmap for high-volume, low-latency data systems (Spark, Kafka, Iceberg, RisingWave, Flink).
• Design and operate scalable data architecture serving trading, risk, compliance, analytics, and product teams.
• Drive AI-powered automation and intelligent workflows across data stacks.
• Partner with ML/AI, analytics, and product teams to deliver platform capabilities.
• Evolve data-lake and warehouse architecture to support batch and streaming workloads.
• Set technical direction balancing reliability, velocity, and cost at scale.
• Hire, mentor, and retain top engineers to build a culture of ownership.

Skills

Python

Scala

Java

Leadership

Remote team management

Data streaming

Distributed systems

Tools

RisingWave

Kafka

Spark Streaming

Iceberg

Parquet

Presto

Flink

Debezium

Job description

The Team

Favia's Data Platform team builds the real-time infrastructure that powers decision-making across one of the world's largest digital asset exchanges. We operate at the intersection of streaming data, large-scale platform engineering, and AI-driven automation — processing billions of events daily across trading, compliance, and product systems.

This role leads the team responsible for Favia's streaming and data platform layer — designing systems that move, transform, and serve data in real time. You'll own the architecture around stream processing (RisingWave, Flink), drive adoption of AI-powered automation and workflows across the data stack, and build the platform primitives that the rest of engineering depends on.

The opportunity

• Lead and grow a team of senior data platform engineers building Favia's real-time streaming infrastructure

• Own the architecture and roadmap for high-volume low-frequency data systems, with focus on data stack like Spark, Kafka, Iceberg, RisingWave, Apache Flink

• Design and operate scalable data architecture that serve trading, risk, compliance, analytics and many product teams.

• Drive adoption of AI automation and intelligent workflows — automating data quality checks, pipeline orchestration, anomaly detection, and self-healing infrastructure

• Partner with ML/AI, analytics, and product engineering teams to deliver platform capabilities that accelerate their work

• Evolve Favia's data-lake and warehouse architecture to support both batch and streaming workloads seamlessly

• Set technical direction for the team — balancing reliability, velocity, and cost efficiency at scale

• Hire, mentor, and retain top-tier platform engineers; build a culture of ownership and technical excellence

What You Bring

• 8+ years in data engineering, platform engineering, or distributed systems — with at least 3 years managing engineering teams

• Experience and knowledge of building data-lakes in AWS (i.e. Spark, Athena, Iceberg, Parquet, Presto), including data modeling, data quality best practices, and self-service tooling.

• Strong expertise in building and operating real-time data at scale including Kafka, Spark Streaming, Debezium, and CDC pipelines.

• Proven ability to manage competing priorities across multiple stakeholder groups — aligning platform investments with the needs of product, finance, compliance, analytics, and other teams

• Strong communicator — able to explain risks, trade-offs, and roadmap decisions to both senior technical audiences and non-specialist stakeholders.

• Experience designing or adopting AI/ML-powered automation in data workflows — pipeline orchestration, intelligent monitoring, automated remediation, or LLM-integrated tooling

• Proficiency in Python, Scala, or Java in a production data platform context

• Solid understanding of cloud-native data infrastructure (AWS preferred — Glue, Athena, S3, EMR, Lambda, or equivalents)

• Track record of managing, recruiting, and developing high-performing remote engineering teams

• Ability to translate long-term platform vision into executable quarterly roadmaps

• Servant-leadership style — you coach, unblock, and grow your engineers

• AI-ready to 10X the team efficiency and overall output.

Nice to haves

• Experience with RisingWave and/or Clickhouse specifically — either in production or in serious evaluation

• Familiarity with LLM-based agents or AI workflow frameworks (e.g. LangChain, LangGraph, custom orchestration)

• Background in cryptocurrency, trading systems, or high-throughput financial data

• Experience building self-service data platform tooling for internal engineering consumers

• Contributions to open-source streaming or data infrastructure projects

Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis.

Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution.

We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.

Our commitment

We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision.

As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws.