Overview
Data Engineers within our Data capability team are often working on:
* Analysing customer requirements in long-term projects and new bid work to uncover opportunities for customers to leverage their data.
* Engineering and automating resilient, scalable data platforms and pipelines using tools like Apache Spark, Apache NiFi, and Kubeflow.
* Working with a variety of datastores, including relational (SQL), NoSQL (Elasticsearch, MongoDB), and Graph Databases (Neo4j).
* Analysing and modelling complex customer data, performing statistical analyses, and designing cleansing, transformation, and normalisation processes.
* Deploying and managing ML/AI models and environments using frameworks such as TensorFlow and PyTorch.
* Writing and supporting high-quality software solutions in Python to implement data science models, tools, and techniques.
* Leveraging cloud platforms like AWS, Azure, and GCP to build and deploy robust data solutions.
Responsibilities
As a Data Engineer, you will help maintain our strong reputation for delivering robust solutions by taking a conscientious and scientific approach to customer data challenges. You will use your strong problem-solving skills to design and develop innovative techniques and tools in an agile manner. Working collaboratively with other data engineers, data scientists, and developers, you will be responsible for building the foundational systems and connective tissue that make our data science work possible. A key part of our culture here at Naimuri is continuous improvement via mentoring and supporting earlier-career colleagues, helping to foster a culture of continuous learning and shared expertise across the team. You will work closely with customers and internal teams to:
* Design, build, and maintain data ingestion and transformation pipelines.
* Investigate, transform (with provenance), and model customer data, performing data cleansing and feature engineering to prepare data for analysis. This may be with tools such as Apache NiFi, or libraries such as Pandas (Python).
* Work with data architects and platform engineers to design and implement secure, scalable data storage and processing solutions.
* Apply statistical methods to analyse customer data using libraries such as NumPy and SciPy.
* Identify opportunities to design and build algorithms to transform and interrogate data at scale.
* Collaborate with Data Scientists to productionise ML/AI models, ensuring they are efficient, scalable, and maintainable.
* Develop data visualisations and reporting tools for audiences of different technical abilities, using libraries like Matplotlib.
* Test and compare the effectiveness of different computational techniques and database technologies for working with data.
Qualifications
* Has experience of working with and is passionate about building robust, scalable systems to handle complex data.
* Takes a conscientious, curious, and scientific approach to their work.
* Continually learning about state-of-the-art techniques in technology, academic, and industry articles.
* Strong programming skills, particularly in Python.
* Hands-on experience with relational databases (e.g. SQL) and/or NoSQL or distributed database technology (e.g., Elasticsearch, MongoDB, Neo4j).
* A solid understanding of data modelling, data cleansing, and data engineering principles, and potentially other processes such as:
o Data quality monitoring
o Performance monitoring and tuning
o Change data capture/audit/generation and sync of derived data sets
o Schema design and migrations
* Strong analytical and problem-solving abilities.
* The ability to communicate complex technical ideas to diverse audiences.
* A degree in a field like Computer Science, Data Science, Engineering, Mathematics, or Physics (though we value demonstrable experience just as much!).
* Experience designing and developing data ingestion and transformation pipelines using tools like Apache Spark or cloud-native solutions in AWS, Azure, or GCP.
* Familiarity with the lifecycle of ML/AI models and experience with MLOps tools like Kubeflow/MLflow.
* Experience designing and running batch processing or streaming jobs.
* Experience with Graph Databases (e.g., Neo4j).
* Familiarity with data science and machine learning libraries (Scikit-learn, NLTK, spaCy).
* Experience creating Python-based applications and/or APIs (e.g. using Pydantic).
* Familiarity with data governance and lineage at both a conceptual and implementation level.
Benefits
* Flexible/Hybrid working options
* A company performance related bonus
* Pension matched 1.5x up to 10.5%
* AXA group 1 medical cover
* Personal training budget
* Holiday buy-back scheme
* A flexible benefits scheme
Note: Naimuri is offering the chance to help make the UK a safer place through innovation. We partner with government and law enforcement on some of the most challenging data and technology problems out there, and we\'re looking for a Data Engineer to join our mission. We are based in Salford Quays, Manchester, with satellite teams in London and Gloucestershire. We offer hybrid working with a maximum typically of one or two days per week on site, depending on team needs. Our core hours are 10:00am - 3:00pm, and office hours are 7:30 - 18:00, Monday to Friday. Our salary is competitive and depends on experience, with consideration of seniority during interviews.
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