Senior Data Engineer - Analytics @ Morgan Stanley

Job Description

Job Description: Life at Grab At Grab, every Grabber is guided by The Grab Way, which spells out our mission, how we believe we can achieve it, and our operating principles - the 4Hs: Heart, Hunger, Honour and Humility. These principles guide and help us make decisions as we work to create economic empowerment for the people of Southeast Asia. Get to know our Team The Data Engineering team 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 developers that strives to solve all kinds of data related problems faced by teams Grab-wide. Along with the growth of Grab, our team continues to learn, innovate and expand our suite of tools and technology to ensure Grab's continued success. Get to know the Role Data Engineers in Grab get to work on one of the largest and fastest-growing datasets of any company in South East Asia. We operate in a challenging. fast-paced and ever-changing environment that will push you to grow and learn. You will be involved in various areas of Grab's Data Ecosystem, including reporting & analytics, data infrastructure, and various other data services that are integral parts of Grab's overall technical stack. The Day-to-Day Activities You are responsible for building, deploying and managing big data solutions that can adequately handle the needs of a rapidly growing data-driven company. You make an impact by leading the development of systems, architectures, and platforms that can scale to the 3 Vs of Big data (Volume, Velocity, Variety). You streamline data access and security to enable data scientists and analysts to access data whenever they need to. You develop scalable and reliable ETL pipelines and processes to ingest data from a large number and variety of data sources. You maintain and optimise the performance of our data analytics infrastructure to ensure accurate, reliable and timely delivery of key insights for decision making. You lead the movement cleaning and normalizing subsets of data of interest as a preparatory step before more in-depth analysis by the data scientists. You will work with high-performance analytical databases and computation engines like Spark, Flink, Presto, Synapse, BigQuery, Greenplum, among others. The Must-Haves You have a degree or higher in Computer Science, Electronics or Electrical Engineering, Software Engineering, Information Technology or other related technical disciplines. You have over 5 years work experience You have demonstrated experience in handling large data sets (multiple PBs) and working with structured, unstructured and geographical datasets. You are knowledgeable in designing high-performance and scalable infrastructure stacks for Big Data Analytics. You possess a 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. You have a hunger for consuming data, new data technologies, and discovering new and innovative solutions to the company's data needs. You possess the willingness and tenacity to get into the thick of the team's work when needed. You are organized, insightful and can communicate your observations well, both written and verbally to your stakeholders to share updates and coordinate the development of data pipelines. Our Commitment We are committed to building diverse teams and creating an inclusive workplace that enables all Grabbers to perform at their best, regardless of nationality, ethnicity, religion, age, gender identity or sexual orientation and other attributes that make each Grabber unique

Employement Category:

Employement Type: Full time
Industry: Internet / E-Commerce
Role Category: Application Programming / Maintenance
Functional Area: Not Applicable
Role/Responsibilies: Senior Data Engineer - Analytics

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Keyskills:   Big Data Data Engineering Data Analytics ETL Database Administration Data Cleaning Data Pipelines