Senior Data Engineer, Knowledge Platform, Foundational Data
SG - Singapore · Singapore
- Pay
- Pay not listed
- Work setting
On-site — work setting source
Location type: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Engineering › Knowledge Platform — team source
Department: Engineering › Knowledge Platform
From the employer’s posting
What you’ll work on
Full postingDesign and build scalable data pipelines and data models
Own data projects end to end, including performance and monitoring
Turn ambiguous data needs into reliable, well-structured solutions
Raise the bar on technical design and execution as a senior team member
From the employer’s posting
Design and build scalable data pipelines and data models that power critical use cases
Own projects end to end, from system and pipeline design through performance, monitoring, and ongoing improvements in data quality and reliability.
turn ambiguous data needs into reliable, well-structured solutions
Raise the bar on technical design and execution as a senior member of the team
Education & alternatives
Essentials - Bachelor’s degree or higher in Computer Science, Computer Engineering or a related field. - At least five years of experience designing and implementing scalable ETL pipelines, across batch and real-time workflows, using technologies such as DBT and Spark
Tools in this posting
- Python
- R
- SQL
- ClickHouse
- Databricks
- dbt
- Kafka
- Snowflake
- Spark
- Airflow
- GCP
Source — Tool mentions in context
- Experience working in financial services, payments, or fintech. - Experience with scripting languages such as Python or R for data analysis and automation. - Certification in data management or related technologies.
- At least five years of experience designing and implementing scalable ETL pipelines, across batch and real-time workflows, using technologies such as DBT and Spark - Strong proficiency in SQL, database management systems, data warehousing, and data modelling for business intelligence, machine learning, and operational needs. - Strong understanding of data schemas, including star, snowflake, normalised, and denormalised designs.
The Knowledge Platform sits at the foundation of Airwallex’s Data and AI strategy. We are evolving traditional data infrastructure into knowledge infrastructure—turning structured and unstructured information into trusted, reusable context that helps people and AI systems make better decisions and take action. You’ll build the platform end to end, from core technologies such as Databricks, Clickhouse, Spark, and Kafka to real-time analytics, knowledge retrieval and indexing, model infrastructure, agent capabilities, and AI interaction history. You’ll also develop the evaluation, annotation, feedback, governance, permission, and freshness frameworks required to operate AI reliably at global financial scale. Our mission is making this ecosystem truly agent-ready. That means enabling teams to explore data through natural language, investigate business drivers in real time, and give AI systems secure access to the context and capabilities they need to support decisions and execute workflows.
- Strong understanding of data schemas, including star, snowflake, normalised, and denormalised designs. - Familiarity with Google Cloud Platform and modern data infrastructure tools, including Databricks and Airflow. - Knowledge of data governance practices, the six key governance pillars, and regulatory requirements in the financial industry.
- Bachelor’s degree or higher in Computer Science, Computer Engineering or a related field. - At least five years of experience designing and implementing scalable ETL pipelines, across batch and real-time workflows, using technologies such as DBT and Spark - Strong proficiency in SQL, database management systems, data warehousing, and data modelling for business intelligence, machine learning, and operational needs.
- Strong proficiency in SQL, database management systems, data warehousing, and data modelling for business intelligence, machine learning, and operational needs. - Strong understanding of data schemas, including star, snowflake, normalised, and denormalised designs. - Familiarity with Google Cloud Platform and modern data infrastructure tools, including Databricks and Airflow.
About Airwallex
Our mission is making this ecosystem truly agent-ready.
In the employer’s words · Read in context · Company website ↗
Posting record
Report an errorActively hiringFirst seen by us 10 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 19, 2026 · 10 days ago
- Recorded sightings
- 68
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
About Airwallex
Airwallex is the AI-native financial operating system for a real-time, intelligent economy. More than 675,000 businesses, including McLaren Racing, Qantas, SHEIN, and TikTok, use us, directly or through our platform partners, to run their financial operations or build and monetize financial products of their own.
We started in Melbourne in 2015 to build the infrastructure global commerce runs on. We're the regulated backbone behind global payments: not by accident, but by design. A decade plus, 85+ licenses, and a financial infrastructure spanning North America, Europe, the Middle East, and Asia-Pacific.
We're co-headquartered in San Francisco and Singapore, with more than 2,700 people across 27 offices. We hire builders with founder-level energy, people who move fast with good judgment, dig in with real curiosity, and make calls from first principles rather than waiting to be told what to do. Read our operating principles to see it in full.
How you'll make impact
Knowledge Platform is building the data foundations that support critical business and AI use cases across Airwallex. You'll own reliable, scalable data solutions end to end while helping raise the bar for technical design and execution.
Design and build scalable data pipelines and data models that power critical use cases across Knowledge Platform teams and business domains.
Partner closely with engineering and cross-functional stakeholders to turn ambiguous data needs into reliable, well-structured solutions that support decision-making and product development.
Own projects end to end, from system and pipeline design through performance, monitoring, and ongoing improvements in data quality and reliability.
Raise the bar on technical design and execution as a senior member of the team, bringing strong engineering judgment, practical problem-solving, and a high standard of ownership.
You'll work from our Singapore office five days a week.
What we're looking for
Essentials
Bachelor’s degree or higher in Computer Science, Computer Engineering or a related field.
At least five years of experience designing and implementing scalable ETL pipelines, across batch and real-time workflows, using technologies such as DBT and Spark
Strong proficiency in SQL, database management systems, data warehousing, and data modelling for business intelligence, machine learning, and operational needs.
Strong understanding of data schemas, including star, snowflake, normalised, and denormalised designs.
Familiarity with Google Cloud Platform and modern data infrastructure tools, including Databricks and Airflow.
Knowledge of data governance practices, the six key governance pillars, and regulatory requirements in the financial industry.
Strong problem-solving, attention to detail, communication, and collaboration skills, including experience working with globally distributed teams.
Understanding of AI and an interest in applying data engineering and AI in practical and creative ways.
Preferred
Experience working with data across distributed or multi-datacenter systems, including data migration, duplication, and consistency challenges.
Experience working in financial services, payments, or fintech.
Experience with scripting languages such as Python or R for data analysis and automation.
Certification in data management or related technologies.
Learn more about your team
The Knowledge Platform sits at the foundation of Airwallex’s Data and AI strategy. We are evolving traditional data infrastructure into knowledge infrastructure—turning structured and unstructured information into trusted, reusable context that helps people and AI systems make better decisions and take action.
You’ll build the platform end to end, from core technologies such as Databricks, Clickhouse, Spark, and Kafka to real-time analytics, knowledge retrieval and indexing, model infrastructure, agent capabilities, and AI interaction history. You’ll also develop the evaluation, annotation, feedback, governance, permission, and freshness frameworks required to operate AI reliably at global financial scale.
Our mission is making this ecosystem truly agent-ready. That means enabling teams to explore data through natural language, investigate business drivers in real time, and give AI systems secure access to the context and capabilities they need to support decisions and execute workflows.
If you want to build the foundation that turns Airwallex’s data into knowledge, knowledge into intelligence, and intelligence into measurable business impact, this is where that work happens.
Applicant Safety Policy: Fraud and Third-Party Recruiters
To protect you from recruitment scams, please be aware that Airwallex will not ask for bank details, sensitive ID numbers (i.e. passport), or any form of payment during the application or interview process. All official communication will come from an @airwallex.com email address. Please apply only through careers.airwallex.com or our official LinkedIn page.
Airwallex does not accept unsolicited resumes from search firms/recruiters. Airwallex will not pay any fees to search firms/recruiters if a candidate is submitted by a search firm/recruiter unless an agreement has been entered into with respect to specific open position(s). Search firms/recruiters submitting resumes to Airwallex on an unsolicited basis shall be deemed to accept this condition, regardless of any other provision to the contrary.
Equal opportunity
Airwallex is proud to be an equal opportunity employer. We value diversity and anyone seeking employment at Airwallex is considered based on merit, qualifications, competence and talent. We don’t regard color, religion, race, national origin, sexual orientation, ancestry, citizenship, sex, marital or family status, disability, gender, or any other legally protected status when making our hiring decisions. If you have a disability or special need that requires accommodation, please let us know.
Source details
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Singapore
Working pattern and location restrictions need checking in the full posting.
- Work authorization
Equal opportunity Airwallex is proud to be an equal opportunity employer. We value diversity and anyone seeking employment at Airwallex is considered based on merit, qualifications, competence and talent. We don’t regard color, religion, race, national origin, sexual orientation, ancestry, citizenship, sex, marital or family status, disability, gender, or any other legally protected status when making our hiring decisions. If you have a disability or special need that requires accommodation, please let us know.
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