JPMorgan Payments Global Industry Advisory - EMEA Vice President London Paris 

United Kingdom, England, London 

677495960

Key Responsibilities

• Design and implement robust, scalable, and efficient data pipelines and architectures on AWS.
• Develop data models and schemas to support business intelligence and analytics requirements.
• Utilize AWS services such as S3, Redshift, EMR, Glue, Lambda, and Kinesis to build and optimize data solutions.
• Implement data security and compliance measures using AWS IAM, KMS, and other security services.
• Design and develop ETL processes to ingest, transform, and load data from various sources into data warehouses and lakes.
• Ensure data quality and integrity through validation, cleansing, and transformation processes.
• Optimize data storage and retrieval performance through indexing, partitioning, and other techniques.
• Monitor and troubleshoot data pipelines to ensure high availability and reliability.
• Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data requirements and deliver solutions.
• Provide technical leadership and mentorship to junior data engineers and team members.
• Identify opportunities to automate and streamline data processes for increased efficiency.
• Participate in on-call rotations to provide support for critical systems and services.

Required qualifications, capabilities, and skills

• Experience in software development and data engineering, with demonstrable hands-on experience in Python and PySpark.
• Proven experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Good understanding of data modeling, data architecture, ETL processes, and data warehousing concepts.
• Experience or good knowledge of cloud native ETL platforms like Snowflake and/or Databricks.
• Experience with big data technologies and services like AWS EMRs, Redshift, Lambda, S3.
• Proven experience with efficient Cloud DevOps practices and CI/CD tools like Jenkins/Gitlab, for data engineering platforms.
• Good knowledge of SQL and NoSQL databases, including performance tuning and optimization.
• Experience with declarative infra provisioning tools like Terraform, Ansible or CloudFormation.
• Strong analytical skills to troubleshoot issues and optimize data processes, working independently and collaboratively.

Preferred qualifications, capabilities, and skills

• Knowledge of machine learning model lifecycle, language models and cloud-native MLOps pipelines and frameworks is a plus.
• Familiarity with data visualization tools and data integration patterns.