Purpose of the role
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.
Accountabilities
- 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.
Assistant Vice President Expectations
- To 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
- If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.
- OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will 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. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.
- Influence or convince stakeholders to achieve outcomes.
All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.
Embark on a transformative journey as a Senior Cloud Data Engineer. At Barclays, our vision is clear – to redefine the future of banking and help craft innovative solutions. Join Barclays at a pivotal moment in our data transformation journey, where this role will help define how enterprise-grade data products power Financial Crime prevention and advanced analytics. You’ll work on high-impact platforms used across the bank, collaborate with senior technologists and data leaders, and help shape scalable cloud data solutions with real enterprise-wide impact.
To be successful as a Senior Cloud Data Engineer, you should have experience with:
Designing and building cloud-native data platforms using managed AWS services, including EC2, ECS/Fargate, EMR, Glue, Lambda, and S3
Architecting modern data lake solutions with a good focus on scalability, resiliency, and cost optimization
Working with open table formats and storage standards such as Apache Iceberg and Parquet
Implementing data catalogs, metadata management, and schema evolution strategies
Designing and optimizing reliable, high-performance ETL/ELT data pipelines
Some other highly valued skills may include:
Experience with Databricks and/or Snowflake for large-scale data processing and analytics
Understanding of data governance practices, including data lineage, data quality controls, and stewardship
Implementing data security and privacy controls such as encryption, access management, and regulatory compliance
Designing high-volume, governed, and performant analytical data stores
Familiarity with financial crime, regulatory, or risk-focused data domains
You may be assessed on the key critical skills relevant for success in this role, such as risk and controls, change and transformation, business acumen, strategic thinking, digital and technology, as well as job-specific technical skills.
This role is located in Whippany, New Jersey.
Minimum Salary: $120,000
Maximum Salary: $175,000
The minimum and maximum salary/rate information above includes only base salary or base hourly rate. It does not include any other type of compensation or benefits that may be available.
Barclays employees are eligible for a suite of competitive and generous employee benefits, including medical, dental and vision coverage, 401(k), life insurance, and other paid leave for qualifying circumstances.
This position is eligible for an incentive award.
Top Skills
Similar Jobs
What you need to know about the NYC Tech Scene
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory



