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Solution Engineer at Digital Divide Data

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Job Detail

  • Job ID 1022107
  • Experience  2 Years
  • Qualifications  Degree Bachelor

Job Description

What you’ll do

  • Design and build robust data ingestion pipelines, transforming raw CSV/TSV data into structured, queryable datasets.
  • Model custom entities and map diverse data sources into standardised target schemas.
  • Build and manage data environments using SQLite, Google Cloud SQL and BigQuery.
  • Develop and maintain Dockerised services for data loading, embedding generation and data-serving applications.
  • Deploy and operate production workloads on Google Cloud Run, with a focus on scalability, reliability and high availability.
  • Work across Redis, VPC networking, Artifact Registry and Cloud Storage.
  • Implement secure cloud architectures using Cloud IAM, VPC and Cloud Run ingress controls.
  • Automate data workflows and deployments through GitHub Actions, including scheduled ingestion, ID mapping, embedding generation and container builds.
  • Build and integrate AI-powered capabilities, including natural-language querying, semantic search, embeddings and LLM-powered workflows.
  • Contribute to emerging agentic architectures and integrations, including technologies such as Model Context Protocol (MCP).

What we’re looking for

You bring:

  • 2+ years’ experience in data engineering, cloud engineering or backend development.
  • Strong Python development skills, including practical experience with Pandas.
  • Solid experience with Docker and containerised applications.
  • Strong working knowledge of Google Cloud Platform, particularly cloud compute, managed databases, data warehousing, networking and IAM.
  • Strong SQL skills and experience working with both relational and analytical data stores.
  • Experience designing, building and consuming REST APIs.
  • A strong engineering mindset, with the ability to work independently, troubleshoot complex problems and take ownership from development through to production.

It’s a plus if you have

  • Experience with AI/ML engineering, particularly embeddings, Sentence Transformers or LLM applications.
  • Exposure to agentic frameworks, MCP or other emerging AI integration patterns.
  • Experience with Flask and Jinja.
  • Familiarity with WSL and Google Cloud Shell.

Why this opportunity?

  • Because you’ll be building more than pipelines.
  • You’ll help create the technical foundation for intelligent, data-driven applications, where secure cloud infrastructure, high-quality data and AI come together.
  • If you’re looking to deepen your expertise in cloud and data engineering while growing into applied AI, this role offers the opportunity to work on that evolution firsthand.

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