Data Engineer (Contract)

JR United Kingdom; Nottingham; On-site; GBP 40,000 - 65,000; Full time

Job summary

A leading technology consultancy is seeking a Data Engineer to assist in transforming their client's data infrastructure. The role requires strong AWS and Python skills to migrate legacy systems and modernize pipelines, contributing to both CRM integration and infrastructure development.

Qualifications

• Proven commercial experience as a data engineer.
• Hands-on, pragmatic, and able to deliver quickly with minimal supervision.
• Ideally, experience migrating legacy environments (e.g., R to Python).

Responsibilities

• Support CRM data engineering requests and monitor data pipelines.
• Migrate R-based data pipelines to Airflow and Terraform workflows.
• Collaborate with engineering teams for system stability.

Skills

AWS

Python

SQL

Terraform

Apache Airflow

Job description

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We are partnering with a client undergoing a critical transformation of their data infrastructure and CRM capabilities. They are seeking a hands-on Data Engineer with strong AWS experience to support two key initiatives: finalising a Braze CRM integration and migrating legacy R-based data pipelines to a modern cloud-native stack.

Support the CRM team with data engineering requests.

QA, deploy, and monitor data pipelines that push third-party formatted data into Braze.

Manage ad hoc CRM data tasks including journey updates and API integrations.

Work extensively within AWS using Lambda, API Gateway, and Python to maintain and enhance integrations.

Analyze and understand existing R-based data pipelines created by data scientists.

Migrate these pipelines into Airflow, dbt, and Terraform workflows.

Modernize and scale legacy infrastructure running on AWS.

Collaborate with engineering teams to ensure a smooth transition and system stability.

Languages & Scripting:

Python (primary scripting language for Lambda functions)

SQL (BigQuery, Redshift)

R (not essential but beneficial for interpreting existing scripts)

AWS services including Lambda, API Gateway, S3, CloudWatch, Kinesis Firehose

Terraform for infrastructure as code

Orchestration & Transformation:

dbt

CRM & Marketing Tools:

Braze (preferred)

Familiarity with other CRM/marketing automation tools such as Iterable or Salesforce Marketing Cloud is a plus

We are partnering with a client undergoing a critical transformation of their data infrastructure and CRM capabilities. They are seeking a hands-on Data Engineer with strong AWS experience to support two key initiatives: finalising a Braze CRM integration and migrating legacy R-based data pipelines to a modern cloud-native stack.

Phase 1: CRM Data Engineering (Month 1)

• Support the CRM team with data engineering requests.

• QA, deploy, and monitor data pipelines that push third-party formatted data into Braze.

• Manage ad hoc CRM data tasks including journey updates and API integrations.

• Work extensively within AWS using Lambda, API Gateway, and Python to maintain and enhance integrations.

Phase 2: Legacy Pipeline Migration (Months 2-3)

• Analyze and understand existing R-based data pipelines created by data scientists.

• Migrate these pipelines into Airflow, dbt, and Terraform workflows.

• Modernize and scale legacy infrastructure running on AWS.

• Collaborate with engineering teams to ensure a smooth transition and system stability.

Languages & Scripting:

• Python (primary scripting language for Lambda functions)

• SQL (BigQuery, Redshift)

• R (not essential but beneficial for interpreting existing scripts)

Cloud & Infrastructure:

• AWS services including Lambda, API Gateway, S3, CloudWatch, Kinesis Firehose

• Terraform for infrastructure as code

Orchestration & Transformation:

• Apache Airflow

• dbt

CRM & Marketing Tools:

• Braze (preferred)

• Familiarity with other CRM/marketing automation tools such as Iterable or Salesforce Marketing Cloud is a plus
  

Candidate Profile

• Proven commercial experience as a data engineer; industry background is not critical.

• Hands-on, pragmatic, and able to deliver quickly with minimal supervision.

• Strong communicator, able to clearly explain technical decisions and project status.

• Willing to take on essential but sometimes "tedious" tasks without hesitation.

• Practical attitude, especially when working with legacy systems or imperfect code.

• Ideally, experience migrating legacy scripting environments (e.g., R to Python) to modern pipelines.