Senior Data Engineer

Senior Data Engineer

GrabTaxi Pte Ltd
3-5 years
Not Specified

Job Description

Job Description :
Get to know our Team:
When you're an engineer at Grab, you are part of the heart and soul of the company. Our passion is anchored in the work that we do, and this is reflected in the impact we make on millions of lives on a daily basis. Our team is empowered by creating amazing services and tools that serve millions of passengers, driving partners, and fellow grabbers.
Get to know the Role:

  • Be the owner of the most complex financial data service platform in the region with millions of transactions a day

  • Innovate and provide analytics products to internal and external customers

  • Define and build up Data Strategy for Vietnam for the next 3-5 years.

The day-to-day activities:

  • Build, deploy and manage big data solutions that can adequately handle the needs of a rapidly growing data driven company

  • Spearhead the development of systems, architectures, and platforms that can scale to the 3 Vs of Big data (Volume, Velocity, Variety)

  • Streamline data access and security to enable data scientists and analysts to easily access to data whenever they need to

  • Build out scalable and reliable ETL pipelines and processes to ingest data from a large number and variety of data sources

  • Maintain and optimize the performance of our data analytics infrastructure to ensure accurate, reliable and timely delivery of key insights for decision making

  • Lead the movement cleaning and normalizing subsets of data of interest as preparatory step before deeper analysis by the data scientists

  • Run Modern high performance analytical databases and computation engines like Spark, AWS Glue, Presto, AWS Athena, Synapse, and others

The must haves:

  • A degree or higher in Computer Science, Electronics or Electrical Engineering, Software Engineering, Information Technology or other related technical disciplines.

  • Experience in handling large data sets (multiple PBs) and working with structured, unstructured and geographical datasets

  • Designed high performance scalable infrastructure stacks for Big Data Analytics

  • Deep understanding of databases and best engineering practices - include handling and logging errors, monitoring the system, 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

  • Real passion for data, new data technologies, and discovering new and interesting solutions to the company’s data needs

  • Excellent communication skills to communicate with the product development engineers to coordinate development of data pipelines, and or any new product features that can be built on top of the results of data analysis.

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