Delivery Lead/Senior Data Engineer

About 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.

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.

Requirements

• Validated experience supporting enterprise data architecture strategies, defining standards and reference architectures, and balancing performance, scalability, and resilience.
• Highly skilled in cloud data architecture and distributed computing paradigms, with extensive applied experience leveraging AWS data platforms such as Glue, Lambda, S3, Redshift, Athena, and Databricks.
• Advanced knowledge of data modeling techniques, including dimensional modeling, schema evolution, and design patterns for analytics, reporting, and downstream data consumption.
• Demonstrated ability to define, implement, and govern data architecture standards, reference architectures, and engineering frameworks across multiple teams.
• Advanced proficiency in Python, PySpark, and SQL, with the ability to guide teams on performance optimization and scalable design, rather than serving solely as a team member contributor.

Qualifications

• Experience supporting DevOps and CI/CD strategies for data platforms using tools such as Jenkins and GitLab, embedding quality, automation, and reliability into delivery pipelines.
• Ambles knowledge of data governance, metadata management, data quality, and data mesh concepts, with the ability to influence enterprise, wide adoption.
• Experience supporting or enabling machine learning and AI workloads, including model training, inference, or feature pipelines in partnership with Data Science or AI teams.
• Considerable understanding of cloud security, IAM, data access controls, and platform governance, with experience implementing fine grained data security using tools such as Immuta.
• Strategic understanding of DBT, Data Build Tool and analytics engineering practices for scalable transformation and modelling.

Skills

• Strategic understanding of DBT, Data Build Tool and analytics engineering practices for scalable transformation and modelling.
• Strategic understanding of DBT, Data Build Tool and analytics engineering practices for scalable transformation and modelling.

Benefits

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.

Pay

Minimum Salary: $170,000
Maximum Salary: $230,000

Schedule

Not specified