Data Engineer - AVP

Barclays•Jefferson, CO

2d•$189,592 - $195,000•Onsite

About The Position

The purpose of the role is to build and maintain the systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure. This role involves advising and influencing decision making, contributing to policy development, and taking responsibility for operational effectiveness. It requires collaboration with other functions/business divisions, leading a team performing complex tasks, and coaching employees. For an individual contributor, this role involves leading collaborative assignments, guiding team members, identifying new directions for assignments, and consulting on complex issues. The role also involves taking ownership for managing risk and strengthening controls, performing work that is closely related to other areas, and engaging in complex analysis of data from multiple sources to solve problems creatively and effectively. Communication of complex information and influencing stakeholders are key aspects of this role.

Requirements

Develop and maintain robust Java-based data pipelines ensuring reliable, complete, and consistent data processing across enterprise systems.
Build enterprise-grade data ingestion and transformation processes leveraging Java, Spark, Kafka, and cloud-native technologies for high-volume workloads.
Lead the Design and Development team for the US Regulatory applications Barclays commitment for FINRA and SEC.
Acted as SME for defining rules driven logic for Regulation like Bluesheets, LOPR, Consolidated Audit Trail System.
Develop robust errors handling mechanisms, data validation frameworks, and monitoring systems to ensure pipeline reliability and data quality throughout the entire data lifecycle.
Responsible for leading a Java development team, including providing technical mentorship, conducting code reviews, establishing development standards, and guiding team members through complex technical challenges.
Optimize pipeline performance through efficient data partitioning, caching strategies, and parallel processing techniques to minimize latency and maximize throughput.
Implement comprehensive logging, alerting, and observability solutions to proactively identify bottlenecks, failures, and performance degradation in real-time.
Collaborate with cross-functional teams to establish data governance standards, security protocols, and compliance measures while maintaining backward compatibility and seamless integration with existing systems.
Design and implement data warehouses and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.
Develop processing and analysis algorithms fit for the intended data complexity and volumes.
Design and develop scalable APIs leveraging Kubernetes for container orchestration and replica management in cloud environments.
Implemented secure application architecture using OAuth2 authentication protocols and JWT token management, supported by comprehensive testing strategies through JUnit and Mockito frameworks, robust logging solutions, and proficient source code management using GitLab and Bitbucket version control systems.

Nice To Haves

Advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness.
Collaborate closely with other functions/ business divisions.
Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function.
Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes
Demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard.
Lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments.
Identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
Take ownership for managing risk and strengthening controls in relation to the work done.
Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively.
Communicate complex information.
Influence or convince stakeholders to achieve outcomes.
Demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship.
Demonstrate the Barclays Mindset – to Empower, Challenge and Drive.

Responsibilities

Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data.
Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.
Development of processing and analysis algorithms fit for the intended data complexity and volumes.
Collaboration with data scientist to build and deploy machine learning models.
Develop and maintain robust Java-based data pipelines ensuring reliable, complete, and consistent data processing across enterprise systems.
Build enterprise-grade data ingestion and transformation processes leveraging Java, Spark, Kafka, and cloud-native technologies for high-volume workloads.
Lead the Design and Development team for the US Regulatory applications Barclays commitment for FINRA and SEC.
Acted as SME for defining rules driven logic for Regulation like Bluesheets, LOPR, Consolidated Audit Trail System.
Develop robust errors handling mechanisms, data validation frameworks, and monitoring systems to ensure pipeline reliability and data quality throughout the entire data lifecycle.
Responsible for leading a Java development team, including providing technical mentorship, conducting code reviews, establishing development standards, and guiding team members through complex technical challenges.
Optimize pipeline performance through efficient data partitioning, caching strategies, and parallel processing techniques to minimize latency and maximize throughput.
Implement comprehensive logging, alerting, and observability solutions to proactively identify bottlenecks, failures, and performance degradation in real-time.
Collaborate with cross-functional teams to establish data governance standards, security protocols, and compliance measures while maintaining backward compatibility and seamless integration with existing systems.
Design and implement data warehouses and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.
Develop processing and analysis algorithms fit for the intended data complexity and volumes.
Design and develop scalable APIs leveraging Kubernetes for container orchestration and replica management in cloud environments.
Implemented secure application architecture using OAuth2 authentication protocols and JWT token management, supported by comprehensive testing strategies through JUnit and Mockito frameworks, robust logging solutions, and proficient source code management using GitLab and Bitbucket version control systems.