Data Engineer

Secretlab; Singapore; On-site; SGD 120,000 - 150,000; Full time

Job summary

Secretlab is seeking a Senior Data Engineer to build and scale our data infrastructure and analytics. You will design data models and data warehouses, implement star-schema analytics, and develop ML layers using tools like Airflow and DBT.

You will ensure reliable pipelines, reduce technical debt, and guide junior team members as we scale our data culture. Join a fast-moving team in a hybrid environment, working with AWS cloud data services, Snowflake, Fivetran, and other modern data stack

Qualifications

• Proficient in SQL and Python for data engineering tasks.
• Experience building and maintaining data pipelines and data models.
• Familiar with cloud platforms and DevOps basics (Git, CI/CD).

Responsibilities

• Set up AWS cloud data infrastructure for data engineering use cases.
• Design data models and architectures for data warehouse and systems.
• Develop star-schema analytics and ML layers with modern tools.
• Maintain reliable data pipelines with testing and logging.
• Collaborate with team and guide junior members.
• Prioritize feature delivery aligned with user stories.

Skills

SQL

Python

Data pipelines

CI/CD basics

Tools

Git

Docker

Terraform

Airflow

DBT

Snowflake

Fivetran

S3

Job description

Secretlab is an international gaming chair brand seating over two million users worldwide, with our key markets in the United States, Europe and Singapore, where we are headquartered.

You will be a Senior Data Engineer/ Data Engineer in our team, responsible for bringing Secretlab's data infrastructure and analytics. The demand for clean serviceable stream/batch data has outstripped our ability to handle out of the box solutions; the demand for information has grown rapidly here at Secretlab. We're looking for Data Engineers who are excited about bringing a start-up data culture to a new level.

Responsibilities:

To be successful

• Setup AWS Cloud data infrastructure for data engineer or data science use-cases
• Secure Data Infrastructure from breaches and lapses (Setup VPC, SAML, according to architectural best practices)
• Design Data Model & Architecture for the data warehouse & other data systems
• Develop star-schema and analytics and ML layers with Airflow, Data Built Tool, etc.
• Develop Standard Template Packages for the rest of the team (e.g. logger templates and AWS, etc.)
• Maintain a reliable data pipeline by following best practices (avoid accruing technical debt by unit testing, logging etc.).
• Have MVPs and balance UI/UX/Function/Reliability - avoiding over or under-engineering pitfalls.
• Build to Order pipelines need to be delivered against feature requests & user stories
• Be comfortable with SaaS like Fivetran, DBT, S3, and Snowflake
• Communicate clearly and concisely about all the aforementioned requirements as well as guide junior team members
• PRs are bite-sized and easy to review with a 50% of PRs to clear within 1 review & 90% after 2 reviews

What your week will look like

• AGILE Sprints with Business Intelligence Team to prune & prioritize backlog (Ops)
• Develop data models (star-schema, event-based data marts, etc.)
• Code reviews are part of the Data Team's production process
• Microbatch / Batch data in from source systems such as Shopify
• Automate DBT pipelines with Orchestrators such' as Airflow/Luigi
• Handle data processing errors and failures as they surface
• Contributing process improvements and tool selections in the weekly retro (start, stop, continue)

Requirements:

Technical

• SQL, Python ProficientFamiliarity with DevOps tools such as Git, Docker, terraform is a plus
• Familiarity with DevOps tools such as Git, Docker, terraform is a plus
• Familiar with error logging, bad record handling, etc.
• Building human-fault-tolerant pipelines understanding how to scale up, addressing continuous integration, knowledge of database administration, maintaining data cleaning and ensuring a deterministic pipeline
• Experience with the cloud (e.g., AWS, GCP)

Personality

• Real passion for data, new data technologies, and discovering new and interesting solutions to the company’s data needs
• Upfront and Candid Personality - someone who is eager to contribute to the continuous improvement of both team and process; open to accepting and giving feedback (especially in retros)
• Honest and Pragmatic - someone who access their capabilities honestly without embellishment
• Prior experience with scaling up start-ups
• Apache-Spark

For more details on this position and other opportunities, please refer to our careers page