Senior Data Engineer — Python & AWS for Real-Time Pipelines

Morgan McKinley; Philippines; Hybrid; PHP 1,500,000 - 2,100,000; Full time

Job summary

Morgan McKinley seeks a Senior Data Engineer to lead strategic data pipelines and calculation engines using Python and AWS serverless tech. You will partner with Risk and Technology teams in London to deliver high-throughput ingestion, transformation, and real-time risk capabilities.

The role emphasizes AI-assisted development, TDD, and robust microservice design. You will work across data, messaging, and cloud platforms with a strong focus on production-grade data systems.

Qualifications

• 7+ years of software/data engineering experience with Python.
• Experience building real-time and batch data pipelines.
• Hands-on with serverless cloud architectures (AWS/Azure).
• Familiarity with microservices, messaging, and data storage (SQL/NoSQL).
• Proficient in TDD, CI/CD, and modern software engineering practices.
• Aware of financial data concepts and risk domain is a plus.

Responsibilities

• Design, build, and operate scalable real-time and batch data pipelines.
• Develop cloud-native, event-driven services using AWS Lambda and Step Functions.
• Leverage AI coding tools to accelerate development and testing.
• Define data models, APIs, and integration patterns for distributed systems.
• Implement end-to-end automation, tests, and robust CI/CD pipelines.

Skills

Python

Event-Driven

Microservices

TDD

CI/CD

Data Pipelines

Problem Solving

Cloud Concepts

Tools

AWS Lambda

AWS Step Functions

S3

DynamoDB

Kafka

PostgreSQL

Terraform

Docker

Job description

Morgan McKinley seeks a Senior Data Engineer to lead strategic data pipelines and calculation engines using Python and AWS serverless tech. You will partner with Risk and Technology teams in London to deliver high-throughput ingestion, transformation, and real-time risk capabilities.

The role emphasizes AI-assisted development, TDD, and robust microservice design. You will work across data, messaging, and cloud platforms with a strong focus on production-grade data systems.