Senior Data Engineer

3 weeks ago


Singapore GXS BANK PTE. LTD. Full time
We are living in exciting times.

Technology is reshaping how we live and we want to use it to redefine how financial services are offered, which is why Singtel and Grab are coming together.

Singtel is Asia's leading communications group connecting millions of consumers and enterprises to essential digital services while Grab is the leading technology company in Southeast Asia offering everyday services to consumers.

Together, we have big dreams to unlock and financial inclusion for people in our region is just one.

We want to build a digital bank with the right foundation - using data, technology and trust to solve problems and serve customers.


Get to know the Role:


As the Senior Data Engineer in the Data Services team, you will be working on all aspects of Data, from Platform and Infra build out to pipeline engineering and writing tooling/services for augmenting and fronting the core platform.

You will be responsible for building and maintaining the state-of-the-art data Life Cycle management platform, including acquisition, storage, processing and consumption channels.

The team works closely with Data scientists, Product Managers, Legal, Compliance and business stakeholders across the SEA in understanding and tailoring the offerings to their needs.

As a member of the Data Services, you will be an early adopter and contributor to various open source big data technologies and you are encouraged to think out of the box and have fun exploring the latest patterns and designs in the fields of Software and Data Engineering.


The day-to-day activities:

  • Build and manage the data asset using some of the most scalable and resilient open source big data technologies like Spark, Airflow, DBT, Kafka,Yarn/Kubernetes, Snowflake, ElasticSearch, Presto/Dremio
  • Design and deliver the nextgen data lifecycle management suite of tools/frameworks, including ingestion and consumption on the top of the data lake to support realtime, APIbased and serverless usecases, along with batch (mini/micro) as relevant
  • Build and expose metadata catalog for the Data Lake for easy exploration, profiling as well as lineage requirements
  • Enable Data Science teams to test and productionize various ML models, including propensity, risk and fraud models to better understand, serve and protect our customers
  • Lead technical discussions across the organization through collaboration, including running RFC and architecture review sessions, tech talks on new technologies as well as retrospectives

The must haves:

  • At least 2+ years of relevant experience in developing scalable, secured, fault tolerant, resilient & missioncritical Big Data platform.
  • Proficiency in at least one of the programming languages Java, Scala or Python along with a fair understanding of runtime complexities
  • Able to maintain and monitor the ecosystem with 99.99% availability
  • Must have sound understanding for all Big Data components & Administration Fundamentals. Handson in building a complete data platform using various open source technologies
  • Must have good fundamental handson knowledge of Linux and building a big data stack on top of AWS/Azure using Kubernetes
  • Strong understanding of big data and related technologies like Spark, Presto, Airflow, Yarn etc
  • Good knowledge of streaming systems like Spark Streaming, Kafka connect or equivalent
  • Experience with NoSQL databases
  • KV/Document/Graph and similar
  • Able to drive Devops best practices like CI/CD, containerization, bluegreen deployments, 12factor apps, secrets management etc in the Data ecosystem
  • Must have the knowledge to build Data metadata, lineage and discoverability
  • Good understanding on the latest developments in the areas of machine learning models and efficiently supporting them is a plus
  • Proven ability to contribute to the open source community and uptodate with the latest trends in the Big Data Space is great to have

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