Lead Data Engineer - Python, Databricks

JP Morgan Chase; Glasgow; On-site; GBP 62,000 - 102,000; Full time

Job summary

JP Morgan Chase in Glasgow is seeking a Lead Data Engineer to design, build and maintain scalable data pipelines using Python and Databricks. The role focuses on enterprise data architectures that enable robust analytics and reporting across business units.

You will drive data quality improvements, implement backup/recovery strategies, and collaborate with cross-functional teams on data requirements and security best practices.

Qualifications

• Formal training or certification on data engineering concepts.
• Hands-on experience developing and maintaining data pipelines using Python.
• Proficiency with Databricks for large-scale data processing and analytics.
• Experience working with relational and NoSQL databases.
• Proficiency across the full data lifecycle, including ingestion, transformation, storage, and access.
• Experience implementing database backup, recovery, and archiving strategies.
• Strong understanding of data quality principles and experience driving root cause analysis for data issues.
• Experience working with enterprise-level datasets in a large, complex organization.
• Familiarity with cloud-based data platforms and modern data architecture patterns.
• Experience in site reliability engineering or infrastructure deployment roles.
• Knowledge of data governance, access control, and security best practices.

Responsibilities

• Design and deliver scalable, secure, and reliable data pipelines using Python and Databricks to support enterprise-level business needs.
• Develop and maintain data models and architectures that enable high-quality analytics and reporting across multiple business functions.
• Drive root cause analysis and corrective action for data quality issues, ensuring consumers can trust the data they rely on.
• Implement and manage database backup, recovery, and archiving strategies to ensure data availability and resilience.
• Evaluate and report on access control processes to determine the effectiveness of data asset security with minimal supervision.
• Collaborate with cross-functional teams to define data requirements and deliver solutions aligned with business objectives.
• Identify opportunities to optimize data workflows and improve overall pipeline performance and efficiency.
• Contribute to a team culture of diversity, opportunity, inclusion, and respect.

Skills

Python

Databricks

Relational DBs

NoSQL databases

Data quality

Data governance

Cloud platforms

SRE / Infra

Security best practices

Root cause analysis

Tools

Databricks

SQL

Cloud platforms

Job description

Salary: £62,000 - 102,000 per year

Requirements:

• Formal training or certification on data engineering concepts and advanced applied experience.
• Hands-on experience developing and maintaining data pipelines using Python.
• Proficiency with Databricks for large-scale data processing and analytics.
• Experience working with both relational and NoSQL databases.
• Proficiency across the full data lifecycle, including ingestion, transformation, storage, and access.
• Experience implementing database backup, recovery, and archiving strategies.
• Strong understanding of data quality principles and experience driving root cause analysis for data issues.
• Experience working with enterprise-level datasets in a large, complex organization.
• Familiarity with cloud-based data platforms and modern data architecture patterns.
• Experience in site reliability engineering or infrastructure deployment roles.
• Knowledge of data governance, access control, and security best practices.

Responsibilities:

• Design and deliver scalable, secure, and reliable data pipelines using Python and Databricks to support enterprise-level business needs.
• Develop and maintain data models and architectures that enable high-quality analytics and reporting across multiple business functions.
• Drive root cause analysis and corrective action for data quality issues, ensuring consumers can trust the data they rely on.
• Implement and manage database backup, recovery, and archiving strategies to ensure data availability and resilience.
• Evaluate and report on access control processes to determine the effectiveness of data asset security with minimal supervision.
• Collaborate with cross-functional teams to define data requirements and deliver solutions aligned with business objectives.
• Identify opportunities to optimize data workflows and improve overall pipeline performance and efficiency.
• Contribute to a team culture of diversity, opportunity, inclusion, and respect.

Technologies:

• Cloud
• Databricks
• Support
• Marketing
• NoSQL
• Python
• Security

More:

We are J.P. Morgan, a global leader in financial services providing strategic advice and products to corporations, governments, wealthy individuals, and institutional investors. We value our people as our strength and foster a culture of inclusion, opportunity, and respect. Our Corporate Functions teams span finance, risk, human resources, and marketing, and play an essential role in setting our businesses, clients, customers, and employees up for success. This is a full-time Lead Data Engineer role in our Compute Infrastructure Platforms team, where we design, build, and maintain critical data pipelines and architectures that support our business objectives.

last updated 36 week of 2026