Data Engineer
Singapore
Lynx Analytics
Integrate ML, Graph AI, & LLMs to uncover, forecast, analyze segment and network dynamics, delivering precise reasoning and insightful recommendations.SUMMARY STATEMENT
The Data Engineer works within a cross-functional project team and is responsible for automating and productizing advanced analytics pipelines. S/he will work with a variety of technologies, including Generative AI, and our proprietary big graph analysis framework.
WHAT YOU’LL DO
A Data Engineer’s responsibility is to implement and deploy data analysis pipelines at various clients of Lynx Analytics. This includes participating in:
- Understanding deeply the business problem that we are trying to solve by our analytical solutions
- Through continuous consultations with employees of our client, discover the client’s existing data sources that are relevant to the problem we try to solve. This includes discussions with client’s IT teams, data owners, future business owners etc.
- Working together with the client’s IT teams to define the technical architecture for the analytical solution that we are to deploy
- Implement the data ingestion subsystem: This is the system responsible for moving all the necessary data sources to a single location where the actual analysis will happen
- Implement the data analysis pipelines
- Integrate the results into business UIs developed by Lynx or pre-existing client software systems
SKILLS AND EXPERIENCE
Skills You Should Have:
- Python (pytest, pre-commit, venv, etc.)
- Airflow, dbt, or other orchestration tool
- Apache Spark, PostgreSQL, BigQuery, or other SQL/NoSQL engines
- Docker, Docker Compose, Terraform or other IaC tools
- Linux OS
- One of major cloud platforms like GCP, AWS, or Azure
What You Might Also Work With:
- CI/CD tools like GitHub Actions
- FastAPI or Flask for service endpoints
- Network setup (DNS, TLS, SSH, IP routes, etc.)
You Might Be a Fit If You:
- Are a generalist who thrives in ambiguity and loves figuring things out.
- Enjoy breaking down big, vague, and unfamiliar problems into concrete actions.
- Value pragmatism over perfection: you look for MVPs, iterative delivery, and quick feedback loops.
- View that DevOps isn’t someone else’s job—you’re comfortable setting up pipelines, fixing flaky builds, or tweaking a reverse proxy config.
- Are comfortable switching hats quickly—from setting up data pipelines and crawling websites to tuning SQL queries or debugging backend servers.
- Are passionate about learning and applying unfamiliar technologies and tools.
- Have some prior experience in Generative AI (ideally RAG) and data science / analytics.
- Get excited about opportunities to travel and work abroad!
Why You’ll Love It Here:
- High ownership, zero micromanagement
- Rapid learning opportunities and diverse challenges
- Flexible work hours, remote-friendly setup
- A collaborative, culture that values real outcomes
- Flat organisational hierarchy with high visibility and accessibility to our leaders
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow Architecture AWS Azure BigQuery CI/CD Data analysis Data pipelines dbt DevOps Docker FastAPI Flask GCP Generative AI GitHub Linux MVP NoSQL Pipelines PostgreSQL Python RAG Spark SQL Terraform
Perks/benefits: Flat hierarchy Flex hours
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