Data Engineer Contract

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.