Best suited to senior data engineers with consultancy or client-facing experience working in data infrastructure and transformation architectures.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from YLD via Greenhouse
YLD is a software engineering and product design consultancy, founded in 2013 based in London, Lisbon and Porto.
We work with engineering and product leaders who know what good looks like and are frustrated by the gap between strategy and execution. We embed senior engineers and designers inside client teams, working in their codebase, their tooling, their delivery rhythm. AI runs through how our teams work, and we help clients adopt it into their own workflows too.
About the role:
We're building out data as a first-class practice at YLD, and we need someone in London who can be the credible technical voice in front of clients and prospects, not just describing what we could do, but backing it with real delivery experience.
This is a senior role, reporting to our Head of Engineering. You'll sit alongside our commercial and client services leadership in meetings where technical credibility matters, help shape and win new engagements, and stay close enough to client work to guide it and step in yourself when an engagement needs you. Alongside, we expect you to build our external reputation in data through events, writing, and the wider community.
About you:
You've been a strong data engineer or data lead for years, and you're comfortable in front of a client as well as in a pull request. You know what good data work looks like well enough to spot it, or its absence, in the first ten minutes of a client conversation. You've probably led a team before. Consultancy background is a strong plus, but not essential if you've got real client or stakeholder exposure elsewhere.
Your day-to-day responsibilities will look like this:
Hands-on delivery (core, from day one)
Doing hands-on data engineering work directly, pipelines, transformation layers, models, and the infrastructure around them, not just guiding others
Adapting to different client contexts: legacy warehouse migrations, greenfield lakehouses, transformation layers that need rescuing
Guiding the wider team and unblocking hard technical problems as your remit grows beyond your own delivery
Defining and evolving our internal standards for data work: testing, documentation, project structure, code review
Mentoring and growing data engineers across the company
Client and commercial (core, from day one)
Joining client and prospect meetings as the technical authority on data, alongside our client services and commercial leads
Shaping proposals and pitches, translating client problems into a credible data approach and a defensible scope
Acting as the escalation point on live data engagements when technical judgement calls need weight behind them
Travelling to client sites for workshops, discovery sessions, and in-person relationship building, and representing YLD at external data events
Practice, talent, and external profile (growth, over the first year)
Owning the growth of YLD's data practice: capability, reputation, and headcount over time
Contributing to attracting and hiring strong data engineers into YLD
Representing YLD at data events and in the wider community as your standing in the market builds
Supporting our sales team so that data becomes something we can proactively sell, not just respond to
You'll have the following skills and experience:
Leadership and commercial
Consulting or agency experience is a strong plus, but real client or stakeholder-facing exposure elsewhere is acceptable
A track record of technical leadership: leading a team or function
Comfortable presenting to senior client stakeholders and holding your own under commercial pressure
Cross-functional fluency: you translate engineering constraints into business terms and negotiate realistic commitments
Appetite to build a public presence in the data community over time, even if you don't have one yet
Technical
Not theoretical, evidenced by things you've actually shipped, and deep enough to set the bar for a team and answer a sceptical client:
SQL as engineering: read and review SQL that performs at scale, and understand query planning, engine quirks, and how materialisation choices affect cost and performance well enough to guide a team's decisions
Python for data: built and maintained production data systems in typed, testable Python, not just notebooks, and can set that standard for others
Data modelling: made deliberate choices between dimensional, Data Vault, normalised and denormalised designs, and can explain the trade-offs in flexibility, query performance, and maintainability to both engineers and clients
Transformation architecture: design transformations that are idempotent, incremental, and dependency-aware. You think in DAGs, not scripts
Pipeline design: weigh batch, streaming, and micro-batch trade-offs against latency, complexity, cost, and reprocessability, and pick the right approach for the problem
Data testing: know what to catch at build time (schema contracts, assertions, transformation logic) versus defer to observability, and can make that call for a team
Data observability: treat data reliability like site reliability, with measurable indicators, alerting, incident response, and root cause analysis
CI/CD for data: version, test, and deploy pipelines like software, with environment promotion, rollback strategies, and infrastructure as code
Data governance: implemented lineage, cataloguing, sensitive data classification, or access control, and can hold a client to account on making data auditable and secure
Cost-conscious: optimised warehouse spend, storage strategies, or job efficiency, and treat compute as a resource to manage, not ignore
Platform fluency: worked across orchestration (Airflow, Dagster), warehouses (Snowflake, BigQuery, Databricks), ingestion (Fivetran, Airbyte, custom), and transformation (dbt, Spark)
AI Native: experienced in agentic coding workflows (context, harness, loop, and graph engineering), and able to embed AI Engineering constructs into pipelines (RAG, semantic search, evals, guardrails, etc)
You should apply if:
Confident and credible in front of clients and prospects, without needing a script, and comfortable holding a firm technical or commercial line when a client or prospect pushes back
Still able to hold up in a deep technical review today, architecture, data modelling, pipeline design, not just talk about decisions you made a few years ago
Self-motivated, and want to own building a practice, not just execute a workstream someone else has defined, and comfortable without a fully defined remit from day one
Able to work well with commercial and client services colleagues who aren't technical themselves, translating for them without talking down
Genuinely energised by variety: different clients, different stacks, different problems, rather than depth in one domain
Happy travelling regularly, client sites, workshops, industry events, wherever the work and the relationship-building actually happens
Benefits you’ll receive:
Company Private Health care (currently provided by Vitality)
Enhanced fully paid maternity and paternity leave for up to 6 months
Company's Pension Scheme
25 days annual holiday (excluding Public Holidays)
£2000 annual allowance for Training/Conferences
£300 annual allowance for additional hardware
Mental Health support
Bonus (depending on Company performance and results)
Company laptop
Generous referral schemes
Our typical Recruitment Process looks like this:
Screening call with the Talent team (45-60 mins)
Introductory conversation with our Head of Engineering (30 mins)
Technical conversation with our Head of Engineering & Data Specialist (60 mins)
Final Interview with our leadership team (60–90 mins)
Get a glimpse of what it's like working at YLD! 🤳
Check out our LinkedIn page
We live and breathe our values, and know you will too:
Growing every day
Including everyone
Relationships built on honesty and ethics
Inspiring solutions
Winning together
We’re an equal-opportunity employer and value diversity in all its forms. We do not discriminate based on race, religion, colour, national origin, gender, sexual orientation, pregnancy or maternity, age, marital status, or disability. We also offer a remote-first working environment, with flexible working and work–life balance as standard for all employees.
Source: YLD careers (Greenhouse)