Junior Data Engineer

Sagacity; Greater London; Hybrid; GBP 50,000 - 80,000; Full time

Benefits offered by this job

Out of Hours allowance

Job summary

Sagacity is seeking a role that blends helpdesk support with data engineering development in a hybrid setup at our London location. You will triage tickets, escalate issues appropriately, and help design, build, and maintain scalable data pipelines and data architectures for client products.

You’ll collaborate with data analysts and scientists, implement ETL processes, ensure data quality, and contribute to governance and reporting.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, IT or equivalent.
• Experience with SQL databases (MySQL, PostgreSQL) and data pipelines.
• Knowledge of ETL concepts, data quality checks and data governance.

Responsibilities

• Answer and triage incoming helpdesk tickets and escalate correctly.
• Assist in designing, building, and maintaining scalable data pipelines.
• Develop APIs and interfaces for data access and manipulation.
• Document processes, pipelines, and architectures; generate data reports.

Skills

SQL

Airflow

Python

Java/Scala

Cloud basics

Data quality testing

Documentation

Education

Bachelor's degree in Computer Science, Engineering, IT

Cloud certifications (AWS/Azure/Google)

Tools

MySQL

PostgreSQL

Apache Airflow

AWS/Azure/Google Cloud

Job description

Location: Hybrid / Monument St, London EC3R 8AJ, UK
job type: Permanent / Full-time
Sector and subsector: IT | Data Engineer
Salary: Competitive salary

This role combines Helpdesk support with data engineering development. You will answer and triage incoming tickets, escalating them to the correct level of support, alongside supporting the design, maintenance, and optimisation of our data pipelines and data architecture for our implemented client products and services. Working closely with data analysts, data scientists, and other stakeholders, you will help ensure the efficient and reliable flow of data across the organisation.

This position includes Out of Hours work. Standard working hours are 6:00am to 2:30pm. There may be times where further Out of Hours coverage is needed,based on a rota; an Out of Hours Allowance is provided for this.

Helpdesk & Support

• Answer and triage incoming helpdesk tickets
• Escalate issues to the correct level of support
• Monitor the helpdesk queue and follow up on outstanding tickets and defects
• Build exposure to client solution queries and investigations, bug fixes, and change controls
• Assist in designing, building, and maintaining scalable data pipelines
• Implement ETL (Extract, Transform, Load) processes to ingest data from various sources
• Ensure data quality, integrity, and reliability through thorough testing and validation

Database Management

• Support the management and optimisation of data storage solutions (e.g. SQL, NoSQL databases, data lakes)
• Monitor and maintain database performance and security

Data Integration

• Collaborate with data analysts and scientists to integrate and consolidate data from multiple sources
• Develop APIs and other interfaces for data access and manipulation

Documentation & Reporting

• Document data processes, pipelines, and architectures
• Generate reports and visualisations to communicate data insights and pipeline performance

Technical Support

• Provide technical support for data-related issues and troubleshoot problems as they arise
• Assist in the implementation of data governance and compliance policies
• Stay up to date with emerging trends and technologies in data engineering
• Participate in code reviews and contribute to the continuous improvement of data engineering practices

What success looks like in the role

• Helpdesk tickets are triaged promptly and accurately, and escalated to the right level without unnecessary back-and-forth
• Data pipelines run reliably, with data quality issues caught through testing before they reach clients
• Data is consolidated cleanly from multiple sources, giving analysts and scientists a dependable foundation to build on
• Processes, pipelines, and architectures are well documented, so knowledge is shared rather than held in one head
• You grow steadily in confidence across the stack, taking on more complex investigations, bug fixes, and change controls over time

Qualifications & Technical Skills

• Proficiency in SQL and experience with relational databases (e.g. MySQL, PostgreSQL)
• Experience with data pipeline and workflow management tools (e.g. Apache Airflow)
• Familiarity with programming languages such as Python, Java, or Scala
• Basic understanding of cloud platforms and services (e.g. AWS, Azure, Google Cloud)
• Knowledge of big data technologies (e.g. Spark) is a plus
• A bachelor's degree in Computer Science, Engineering, Information Technology, or a related field
• Relevant certifications in data engineering or cloud platforms (e.g. AWS, Azure, Google Cloud, Databricks) are a plus