Beamery
Staff Data Engineer

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ABOUT BEAMERY
With the rapid expansion of AI and automation, the future of work has never been more challenging for organizations. Beamery’s unique jobs, skills, and tasks data platform helps organizations navigate these challenges and make more informed decisions across Talent Lifecycle Management. Our solutions power recruitment, mobility, upskilling, diversity, work architecture, and workforce planning for some of the world’s most forward-thinking companies.
We believe that where you work is much more than just a job. Millions of people are being left behind every day in their careers, and we’re on a mission to fix this by creating equal access to meaningful work, skills, and careers for all.
We are an equal opportunity employer committed to building a representative Beamery, creating an equitable, inclusive, and engaging environment for our people.
So, what are you waiting for? Join us and help us transform the future of work once and for all.
What’s ahead — and why it’s an exciting time to join the team:
- Deepening our native integrations with SAP, Workday, Microsoft, and LinkedIn to seamlessly embed our skills intelligence into the platforms where critical workforce decisions are made.
- Embedding our agentic AI to help customers plan smarter for the future—powering workforce strategies, internal mobility, and skills forecasting.
- Advancing our use of proprietary LLMs and knowledge graph technology to help organizations unlock broader talent pools, make fairer decisions, and expand access to opportunity at scale.
But it’s not all about creating high-quality products; we also very much value the company culture we have worked hard to create, built on trust, empathy, and honesty, ensuring our workforce is able to bring their full selves to work.
About the opportunity
Our data platform powers Beamery’s reporting and underpins our AI strategy. We’re hiring a Staff Data Engineer to set its technical direction.
This is our most senior individual contributor role in data engineering. You’ll own the platform’s long-term architecture, make the calls that are expensive to reverse, and lead the work that follows. You’ll also partner with EPD leadership (Engineering, Product, and Design) on work that crosses team boundaries and on keeping the platform aligned with company strategy. The platform exists so everyone at Beamery can make faster decisions with data they trust. The role suits someone energized by ambiguity who measures impact by what the organization can do rather than what they personally shipped.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What will you be doing at Beamery?
- Own the technical strategy for the data platform. Define the multi-quarter architectural vision, build the case for investment with EPD leadership, and sequence delivery incrementally rather than as a big-bang migration. You take on the work with no established playbook and turn it into designs the team can execute. Expect challenges around multi-tenant consistency, correctness at scale, performance ceilings, and data modelling for AI and agentic workloads.
- Architect the analytics, semantic, and AI data layers. Define how core business metrics, feature usage signals, and skills and task intelligence data are modelled, governed, and exposed as trustworthy products to BI, self-service, and AI consumers.
- Set standards that scale beyond your team. Establish the architectural patterns, modelling conventions, and data contracts other teams adopt, favouring guardrails over review gates. Grow senior engineers into stronger technical decision-makers through design review, pairing, and mentorship.
- Own reliability and trust at the platform level. Set our approach to observability, data quality, SLAs, and incident response; lead RCAs on the most serious failures and drive the systemic fixes that prevent recurrence.
What we’re looking for
You’re a staff-level data engineer who has built and run data platforms for internal and external consumers. You’ve built architectures that held up as they grew with a focus on data warehousing, data lakes, and both real-time and batch processing.
Teams bring you their hardest data problems. You’ve made the hard tradeoffs in distributed, multi-tenant systems and lived with the consequences. You’re just as comfortable in production: tracing how one upstream failure ripples through to customers, and making sound calls under pressure.
Your impact isn’t measured in code alone. You’ve led initiatives across team boundaries without formal authority, working directly with principal engineers, platform teams, and data scientists, and treating their constraints as part of your design problem. You’ve made architectural decisions others built on for years, and driven modernization while balancing new technology against real delivery risk. You work with minimal direction, explain tradeoffs and risks credibly to executive audiences, and change your mind as readily as you defend a position.


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Previous professional experience:
- Data transformations using dbt, including patterns for large, complex projects
- Data storage (SQL / NoSQL): schema design, modelling at scale, and multi-tenant isolation
- Back-end engineering: Python (nice to have: Typescript/Node.JS)
- Pipelines: streaming, CDC, correctness, replayability, and evolution over time
- Data quality and observability: validation, testing, data contracts, monitoring, alerting, and incident response
- Infrastructure as code and containerisation (Terraform, Kubernetes)
Our data stack
Our stack will change as we grow, and you’ll be shaping those changes. The ability to learn new tools matters more than experience with any specific one.
- DBT for data modelling and transformation
- BigQuery data warehouse
- Kafka for data streaming between systems
- PostgreSQL & MongoDB for databases
- Typescript/Node.JS on the backend
- Kubernetes
- Python
- Segment for customer-centric event collection
Beamery is open to engage with direct employment or contractors for this position in order to find the right fit candidate to join our team.
Beamery is for Everybody
Diversity and open expression are fundamental to us. We acknowledge the challenges in our industry and strive to develop an inclusive culture where everybody can contribute. We are dedicated to creating an inclusive environment for everyone, regardless of ethnicity, religion, color, sexual orientation, gender identity, race, national origin, age, disability status, or caregiver status. If, for whatever reason, you need us to make reasonable adjustments and adaptations to our recruitment process, please email accommodations@beamery.com
Visit our Diversity, Equality and Inclusion page to learn more about progress and commitments.
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