16 Sep
Data Platform Engineering (Python, Java), Assistant Vice President
North Carolina, Charlotte , 28201 Charlotte USA

Vacancy expired!

Do you want your voice heard and your actions to count? Discover your opportunity with Mitsubishi UFJ Financial Group (MUFG), the 5th largest financial group in the world (as ranked by S&P Global, April 2020). In the Americas, we're 13,000 colleagues, striving to make a difference for every client, organization, and community we serve. We stand for our values, developing positive relationships built on integrity and respect. It's part of our culture to put people first, listen to new and diverse ideas and collaborate toward greater innovation, speed and agility. We're a team that accepts responsibility for the future by asking the tough questions and owning the solutions. Join MUFG and be empowered to make your voice heard and your actions count. Job Summary In this role you will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing and automate data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. Major Responsibilities:

  • Design, build, automate data pipeline, testing systems, event monitoring and notification systems, that implement key aspects of the full data pipeline lifecycle, including acquisition, transformation, management, export, and analytics
  • Triage problems across the data platform to help address development, test, and production issues
  • Assist other engineering groups with data architecture, pipeline development, automation and planning
  • Maintain best practices to facilitate optimized software development and continuous improvement/continuous delivery (CI/CD)
Qualifications
  • Undergraduate degree in computer science, engineering, or a related discipline preferred
  • 5-6 years' experience in data platform engineering, concentrating on data pipeline development and automation, scaling and optimizing Amazon Web Services (AWS) infrastructure, creating and configuring Docker image, and deployment in Redhat Openshift.
  • Experience in the financial services or banking industry preferred
  • Experience implementing enterprise systems with security best practices and site reliability engineering principles.
  • Proficient Primary in Python and secondary in Java.
  • Advanced structured query language (SQL) skills
  • Solid understanding of Linux operating system (OS), networking, and security
  • Strong foundation in OOP and object-oriented design (OOD) principles
  • Strong foundation in AWS Cloud Services and DevSecOps
  • Strong foundation in Docker and Redhat Openshift
  • Experience in developing and automating data pipeline and deployment in Python
  • Experience with developing and configuring AWS CloudWatch, S3, and StepFunction
  • Experience creating and configuring Docker images to increase productivity and efficiency of other data engineers work
  • Experience troubleshooting Linux/Unix shell production systems
  • Preferred candidate with system design thinking, plan and author technical documents, problem solving, and prioritization skills
The above statements are intended to describe the general nature and level of the work being performed. They are not intended to be construed as an exhaustive list of all responsibilities, duties, and skills required of personnel so classified . We are proud to be an Equal Opportunity / Affirmative Action Employer and committed to leveraging the diverse backgrounds, perspectives, and experience of our workforce to create opportunities for our colleagues and our business. We do not discriminate in employment decisions on the basis of any protected category. A conviction is not an absolute bar to employment. Factors such as the age of the offense, evidence of rehabilitation, seriousness of violation, and job relatedness are considered in all employment decisions. Additionally, it's the bank's policy to only inquire into a candidate's criminal history after an offer has been made. Federal law prohibits banks from employing individuals who have been convicted of, or received a pretrial diversion for, certain offenses.

Vacancy expired!

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