MoneyLion
FinTech
SeniorDataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Engineer at MoneyLion. Skills: Data engineering, Big data, Data pipelines, SQL optimization. Design analytics platform. Implement analytics platform”
Industry & Context.
Optimise SQL queries; Simplify data processing
What They're Looking For.
Must Have
Expert at writing and optimising SQL queries, Proficiency in Python, Java or similar languages, Familiarity with data warehousing concepts, Experience in Airflow or other workflow orchestrators, Familiarity with basic principles of distributed computing, Experience with big data technologies like Spark, Delta Lake or others, Proven ability to innovate and leading delivery of a complex solution, Excellent verbal and written communication, Ability to work with shifting deadlines in a fast-paced environment
Nice to Have
Authoritative in ETL optimisation, designing, coding, and tuning big data processes using Spark, Knowledge of big data architecture concepts like Lambda or Kappa, Experience with streaming workflows to process datasets at low latencies, Experience in managing data - ensuring data quality, tracking lineages, improving data discovery and consumption, Sound knowledge of distributed systems, Experience in working with large databases, efficiently moving billions of rows, and complex data modelling, Familiarity with AWS is a big plus, Experience in planning day to day tasks, knowing how and what to prioritise and overseeing their execution
What You'll Do.
Design analytics platform
Implement analytics platform
Operate analytics platform
Improve analytics platform
Design data solutions
Collaborate with data scientists
Collaborate with business analysts
Collaborate with product managers
Collaborate with software engineers
Collaborate with other data engineers
Develop deployed data solutions
Implement deployed data solutions
Validate deployed data solutions
Maintain data warehouse
Maintain data pipelines
Understand data engineering best practices
Implement data engineering best practices
Improve standards for code maintainability
Manage standards for code maintainability
Teach standards for code maintainability
Improve standards for code performance
Manage standards for code performance
Teach standards for code performance
Mentor junior engineers
Provide guidance to junior engineers
How You'll Work.
Team & Collaboration
Data scientists; Business analysts; Product managers; Software engineers; Data engineers
Communication Scope
Summarise complex analyses
Full Job Description
About the Role The 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 Responsibilities - Design, implement, operate and improve the analytics platform - Design data solutions using various big data technologies and low latency architectures - Collaborate with data scientists, business analysts, product managers, software engineers and other data engineers to
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