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Data Engineer

Posted April 13, 2026
Full-time Entry Level

Job Overview

Join Our Dynamic Team as a Data Engineer đźŚź 

Are you passionate about telecoms? Do you thrive in a fast-paced, innovative environment? At Babble, we’re on a mission to be our customer’s most trusted advisor for cloud-based technologies. We’re looking for passionate and talented individuals to join our dynamic team. If so, we have the perfect opportunity for you!  

What will you be doing? 

We need a Data Engineer to develop, maintain, and enhance our Snowflake data platform. You'll build reliable pipelines, create quality transformations, and support analytics for business reporting. Work closely with analysts, stakeholders, and senior engineers to provide accurate, well-documented data for decision-making.

Accountabilities and Deliverables: 

  • Build and maintain scalable ELT pipelines in Snowflake, using OpenFlow and native capabilities.
  • Develop and maintain data models following a Lakehouse and medallion-style approach.
  • Write efficient, readable SQL to transform, test and optimise data for analytics and reporting use cases.
  • Implement data quality checks, validation rules and basic monitoring within pipelines.
  • Support and enable reporting and self-service analytics within the Business Intelligence tooling by delivering well-structured, reliable datasets and semantic layer.
  • Monitor pipeline performance and Snowflake usage and make pragmatic improvements to reliability and cost efficiency.
  • Maintain clear documentation for pipelines, datasets and business logic.
  • Work with analysts, product teams and stakeholders to understand data requirements and translate them into robust data solutions.
  • Follow established engineering standards, version control and delivery processes within the data team.

Core Competencies:

  • Pipelines run reliably and are easy for others to understand and maintain.
  • Data used in business intelligence tooling is trusted, consistent and clearly defined.
  • Issues are identified early through sensible checks and monitoring.
  • Stakeholders understand where their data comes from and how to use it.

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