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Cybersecurity Lead Data Engineer



Data Science
Plano, TX, USA
Posted on Friday, June 28, 2024

Job Description

Join us as we embark on a journey of collaboration and innovation, where your unique skills and talents will be valued and celebrated. Together we will create a brighter future and make a meaningful difference.

As a Lead Data Engineer at JPMorgan Chase within the Cyber and Tech Controls line of business, you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. As a core technical contributor, you are responsible for maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

  • Generates data models for their team using firmwide tooling, linear algebra, statistics, and geometrical algorithms
  • Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way
  • Implements database back-up, recovery, and archiving strategy
  • Evaluates and reports on access control processes to determine effectiveness of data asset security​ with minimal supervision
  • Influences peers and project decision-makers to consider the use and application of leading-edge technologies
  • Works with stakeholders and business leaders to understand reporting needs and recommend tactical and strategic solutions
  • Develops secure, efficient and maintainable production code and review and debugs code written by others
  • Supports data consumption from on premise and cloud based sources
  • Performs automated data quality analysis to identify anomalies and provide a robust solution
  • Adds to team culture of diversity, equity, inclusion, and respect

Required qualifications, capabilities, and skills

  • Formal training or certification on data engineering concepts and 5+ years applied experience
  • Working experience with both relational and NoSQL databases​
  • Experience and proficiency across the data lifecycle
  • Experience with database back-up, recovery, and archiving strategy
  • Deep experience with SQL query language and ETL systems
  • Experience presenting and delivering visual data
  • Proficient knowledge of linear algebra, statistics, and geometrical algorithms

Preferred qualifications, capabilities, and skills

  • Skilled in planning, designing, and implementing enterprise level data analysis solutions
  • Experience with modern data abstraction and federated query tooling
  • Advanced in one or more programming languages (Python, Java, Shell Script)
  • In-depth knowledge of the financial services industry, their compliance requirements and IT systems