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Data Engineer

Aiimi

Milton Keynes

On-site

GBP 40,000 - 70,000

Full time

18 days ago

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Job summary

An exciting opportunity awaits a mid-level Data Engineer at a forward-thinking company, where you will engage in diverse projects across the UK. This role emphasizes collaboration with business experts to uncover valuable insights from data, enabling clients to enhance decision-making and service delivery. You will leverage your expertise in Python, SQL, and the Azure ecosystem to design and optimize data pipelines, ensuring data quality and scalability. With a commitment to personal development and flexible working arrangements, this innovative firm promotes a culture of continuous learning and growth, making it an ideal environment for driven professionals eager to make an impact.

Benefits

25 Days holiday
Flexible working
Promote training and personal development
Bi-annual company retreats

Qualifications

  • Proven experience as a data engineer with a focus on data pipelines and quality.
  • 1-3 years of experience with Oracle and solid SQL understanding.

Responsibilities

  • Collaborate with business experts to extract insights from data.
  • Develop and optimize data pipelines and processing jobs.
  • Support data science teams in data acquisition.

Skills

Python
SQL
Oracle
Data transformation
Data quality assurance
Communication

Tools

Azure
Databricks

Job description

Aiimi is seeking a mid-level Data Engineer to join our Aiimi Services division for an exciting project, collaborating directly with one of our clients.

We work with many clients across the UK, offering diverse projects with unique challenges. You should have a strong interest in learning and working with the latest technologies. As a Data Engineer, you will be a self-driven professional with solid experience in Python, SQL, Oracle and the Azure stack.

A day in the life of an Aiimi Data Engineer:

  • You will be responsible for collaborating with business subject matter experts to discover the information hidden in various sources of content and data, helping our clients make smarter decisions to reduce service failure and deliver better outcomes to their customer base.
  • Your primary focus will be connecting to and extracting data from source systems, applying business logic in the form of data transformations to extract insights from the data and making the data available to the end users so that these insights can be acted on.
  • Supporting strategic planning.
  • Capturing data requirements from both customer and technical teams.
  • Identifying and implementing new data collection processes to include all relevant information.
  • Developing new and innovative ways of working in order to drive efficiencies in the business.
  • Setting up interfaces to source systems and/or working with system owners to facilitate it.
  • Setting up data processing jobs to clean and transform data.
  • Orchestrating and optimising data pipelines.
  • Identifying root cause issues of poor data quality and working with data owners to help remedy.
  • Securing data access.
  • Supporting data science teams and other users in their data acquisition.
  • Creating data models.
  • Ensuring new models, reports and data architectures are promoted and published to centralised self-service data warehouses as required.
Requirements

  • Proven experience as a data engineer, specialising in designing and optimising data pipelines, ensuring data quality, and delivering scalable solutions to support data-driven decisions.
  • Highly proficient in Python.
  • 1-3 years experience with Oracle.
  • Solid understanding of SQL, including analytic functions & database query performance tuning.
  • Proficient in the Azure ecosystem, including expertise in Databricks, Data Warehouse solutions, and related services.
  • Strong communicator and ability to work with key stakeholders.
Benefits

  • 25 Days holiday (excluding bank holidays) - increasing by a day every 2 years.
  • Flexible working.
  • Promote training and personal development.
  • Bi-annual company retreats.
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