Senior Data Engineer - MoneyLion

About the RoleThe Kuala Lumpur office is the technology powerhouse of MoneyLion. We pride ourselves on innovative initiatives and thrive in a fast paced and challenging environment. Join our multicultural team of visionaries and industry rebels in disrupting the traditional finance industry!At MoneyLion, we measure everything and rely on data to guide our decisions, including both long-term strategies and day-to-day operations. As a Senior Data Engineer, your main goal is to support data scientists, analysts and software engineers by providing maintainable infrastructure and tooling they can use to deliver end-to-end solutions to business problems. You will work with terabytes to petabyte-scale data, in a complex data environment supporting multiple products and data stakeholders across the US and <KL.You> will be responsible for designing and implementing an analytical environment using in-house and third-party tools, using Python and/or Java to automate data activities and enable efficient processing of data that is growing in both volume and complexity. You will design and implement complex data pipelines and data models for analytical consumption. You will work with Redshift, Snowflake, EMR, Kubernetes, Airflow and more as the main tools of the job. You will write scalable and performant SQL queries running over billions of rows of data, and help simplify these processing to enable insights to be more easily extractable from them. You should have deep experience in designing and managing large datasets and pipelines to enable business use-cases. You should be an authority at designing, implementing and operating solutions that are scalable, stable and cost-efficient. Key ResponsibilitiesDesign, implement, operate and improve the analytics platformDesign data solutions using various big data technologies and low latency architecturesCollaborate with data scientists, business analysts, product managers, software engineers and other data engineers to develop, implement and validate deployed data solutions. Maintain the data warehouse with timely and quality dataBuild and maintain data pipelines from internal databases and SaaS applicationsUnderstand and implement data engineering best practicesImprove, manage, and teach standards for code maintainability and performance in code submitted and reviewed Mentor and provide guidance to junior engineers on the jobAbout YouExpert at writing and optimising SQL queriesProficiency in Python, Java or similar languagesFamiliarity with data warehousing conceptsExperience in Airflow or other workflow orchestratorsFamiliarity with basic principles of distributed computingExperience with big data technologies like Spark, Delta Lake or othersProven ability to innovate and leading delivery of a complex solutionExcellent verbal and written communication - proven ability to communicate with technical teams and summarise complex analyses in business termsAbility to work with shifting deadlines in a fast-paced environmentBonus PointsAuthoritative in ETL optimisation, designing, coding, and tuning big data processes using SparkKnowledge of big data architecture concepts like Lambda or KappaExperience with streaming workflows to process datasets at low latenciesExperience in managing data - ensuring data quality, tracking lineages, improving data discovery and consumptionSound knowledge of distributed systems - able to optimise partitioning, distribution and MPP of high-level data structures Experience in working with large databases, efficiently moving billions of rows, and complex data modellingFamiliarity with AWS is a big plusExperience in planning day to day tasks, knowing how and what to prioritise and overseeing their executionWhat's Next...After you submit your application, you can expect the following steps in the recruitment process:Online Preliminary Codility testRecruiter Screening CallTake-home Assessment Take Home Discussion (Virtual)Interview - Hiring Manager (Virtual or face-to-face), 1.5 hours