Secretlab is an international gaming chair brand seating over a million users worldwide, with our key markets in the United States, Europe and Singapore, where we are headquartered.
We're looking for a Senior Data Engineer to own the design, build, and delivery of analytics solutions that drive business decisions. Beyond writing SQL, we need someone who understands
why
the business needs data — someone who can translate business problems into well-architected solutions.
This role sits within the
Data Engineering team
but specializes in
Analytics Engineering
— you'll be the technical leader establishing how we model, transform, and serve data to the business. You'll work across Supply Chain, Finance, Marketing, and Operations to translate ambiguous business problems into clean, maintainable data models. You'll partner closely with BI leads, analysts, and business stakeholders to ensure your work creates durable value.
A note on what "good" looks like here:
We care deeply about
modular, scalable design
. Code that works today but can't be easily modified tomorrow creates long-term maintenance burden. If adding a new market or tweaking a calculation requires significant rework, we'd consider that a design gap. We want engineers who build systems that are easy to extend, easy to understand, and easy for others to maintain.
You'll be expected to
own outcomes
— not just ship code, but ensure your work solves real business problems. If you're someone who thrives on building scalable data models, mentoring others, and establishing engineering standards, this role is for you.
To be successful:
Technical Delivery \& Design
Design and own
end-to-end analytics architecture
— star schemas, dimensions, facts, and marts
Write
modular, loosely-coupled code
— changes to one component shouldn't require rewriting others
Deliver medium-to-high complexity projects independently with minimal support
Balance MVP discipline with quality — ship, learn, iterate
Technical Leadership
Drive the Analytics Engineering Center of Excellence
— establish modeling standards, testing patterns, and documentation practices
Mentor and coach junior engineers through code reviews and active skill development
Develop reusable patterns and macros that elevate the whole team's output
Communication \& Stakeholder Partnership
Partner with BI leads, analysts, and business stakeholders to translate requirements into solutions
Own the "what" and "why" behind data models — not just the "how"
Communicate concisely: all updates include
TL;DR → Impact → CTA
Escalate blockers early — we value communication over solo problem-solving
What will your week look like?
Sprint planning
with BI and Analytics team to refine requirements and prioritize work
Data modeling
— designing and building star schemas, event-based marts, and feature tables
Code reviews
— both giving and receiving, with a focus on mentoring and standards
Stakeholder collaboration
— partnering with business teams to validate requirements and outputs
Center of Excellence
— maintaining modeling standards, updating templates, coaching sessions
Requirements:
Technical — Must Have
Strong SQL
— window functions, CTEs, query optimization
dbt proficiency
— models, tests, macros, documentation
Cloud data warehouse
— Snowflake strongly preferred
Data modeling
— star schema, slowly changing dimensions, grain definition
Git
— branching strategies, PRs, code review best practices
Python
— scripting, automation, data validation
Technical — Nice to Have
Ingestion tools (Fivetran, Meltano), orchestration (Airflow), infrastructure (Terraform, Docker, AWS)
Exposure to eCommerce data sources (Shopify, Klaviyo, Google Analytics)
Personality
Ownership mindset
— accountable for outcomes, not just outputs
Clear communicator
— distills complexity for non-technical stakeholders
Honest and pragmatic
— admits when they don't know something
Teacher mentality
— enjoys helping others grow