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Jobs in Singapore   »   Jobs in Singapore   »   Information Technology Job   »   Senior Lead Data Engineer
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Senior Lead Data Engineer

Jpmorgan Chase Bank, N.a.

DESCRIPTION/RESPONSIBILITIES:

We know that people want great value combined with an excellent experience from a bank they can trust, so we launched our digital bank, Chase UK, to revolutionize mobile banking with seamless journeys that our customers love. We're already trusted by millions in the US and we're quickly catching up in the UK – but how we do things here is a little different. We're building the bank of the future from scratch, channeling our start-up mentality every step of the way – meaning you'll have the opportunity to make a real impact.


As a Senior Lead Data Engineer at JPMorgan Chase within the International Consumer Banking, you will be a part of a flat-structure organization. Your responsibilities are to deliver end-to-end cutting-edge solutions in the form of cloud-native microservices architecture applications leveraging the latest technologies and the best industry practices. You are expected to be involved in the design and architecture of the solutions while also focusing on the entire SDLC lifecycle stages.


Our Engineering team is at the heart of this venture, focused on getting smart ideas into the hands of our customers. We're looking for people who have a curious mindset, thrive in collaborative squads, and are passionate about new technology. By their nature, our people are also solution-oriented, commercially savvy and have a head for fintech. We work in tribes and squads that focus on specific products and projects – and depending on your strengths and interests, you'll have the opportunity to move between them.


Job responsibilities

• Provides recommendations and insight on data management, governance procedures, and intricacies applicable to the acquisition, maintenance, validation, and utilization of data​​

• Designs and delivers trusted data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way

• Defines database back-up, recovery, and archiving strategy

• Generates advanced data models for one or more teams using firmwide tooling, linear algebra, statistics, and geometrical algorithms

• Approves data analysis tools and processes​

• Creates functional and technical documentation supporting best practices​​

• Advises junior engineers and technologists

• Evaluates and reports on access control processes to determine effectiveness of data asset security​

• Adds to team culture of diversity, equity, inclusion, and respect


Required qualifications, capabilities, and skills

• Bachelor’s degree or equivalent in computer science or related fields

• Minimally 5 years of experience on data engineering

• Working experience with both relational and NoSQL databases​

• Advanced understanding of database back-up, recovery, and archiving strategies

• Advanced knowledge of linear algebra, statistics, and geometrical algorithms

• Experience presenting and delivering visual data

• Deep understanding of distributed systems and cloud technologies (AWS, GP, Azure, etc.)

• Experience in the all stages of software development lifecycle (requirements, design, architecture, development, testing, deployment, release and support)

• Experience with large scale datasets, data lake and data warehouse technologies on at least TB scale (ideally PB scale of datasets) with at least one of {BigQuery, Redshift, Snowflake}

• Ability to work in a dynamic, agile environment within a geographically distributed team

• Experience in leading a small team of technologists to manage and resolve technical items within expertise


Preferred qualifications, capabilities, and skills

• Experience with a scheduling system (Airflow, Azkaban, etc.)

• Understanding of (distributed and non-distributed) data structures, caching concepts, CAP theorem

• Understanding of security frameworks / standards and privacy

• Experience in automating deployment, releases and testing in continuous integration, continuous delivery pipelines

• Experience with containers and container-based deployment environment (Docker, Kubernetes, etc.)

• A solid approach to writing unit level tests using mocking frameworks, as well as automating component, integration and end-to-end tests


To apply for this position, please use the following URL:

https://ars2.equest.com/?response_id=a0d95a115f22069379a0cc4107c82d1d

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