Senior Data Engineer (Infrastructure)

Get to know our Team:

Data Engineering runs the code, pipeline and infrastructure that extracts, processes and prepares every piece of data generated or consumed by Grab’s systems. We are a diverse team of software engineers that not only work to solve all kinds of data related problems faced by teams from all corners of Grab but we also act as a bridge that ties everyone together through data. As data in Grab never stops growing, this team also never stops, learning, innovating and expanding so that we can bring in or build the latest and best tools, technology to ensure the company’s continued success. ​

Get to know the Role:

If you're a SysOps, DevOps or Sysadmin looking to make the jump into the world of big data, or a Big Data Engineer interested in infrastructure, tooling and automation - this role is tailor made for you!

• Designing, evaluating, and implementing framework that can adequately handle the needs of a rapidly growing data driven company

• Architecting and scaling data analytics infrastructure on AWS; finding opportunities to improve and optimize the workloads, processes to ensure that performance levels can support continuous accurate, reliable and timely delivery of key insights

• Building, designing and deploying ETL pipelines

• Manage continuous uptime of Data services by implementing High Availability tools and best practices

• Manage the continuous testing and deployment of data pipelines, new data services and analytical reporting dashboards.

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

• Partner data scientists and engineers by leading the movement cleaning and normalizing subsets of data of interest as preparatory step to prepare the rich data for deeper analysis on how to improve user experience for Grab customers around the region.

Must haves:

• >5 years of hands-on experience, preferably in data infrastructure

• Experience in container management and orchestration tools like ECS, Kubernetes, and Mesos is a strong plus

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

• Proficiency in Hadoop, Kafka and Spark databases in a large scale environment

• Well versed in setting up continuous integration and deployment for big data or other projects.

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

• Comfortable with Linux Systems Administration

• Deep understanding on 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