Job Title: Data Engineer
Salary:£75,000 - £85,000 D.O.E
Location: London (Hybrid 3days in the office)
Job Type: Full Time, Permanent

Urban Empire Recruitment has partnered with a start-up company that is a disrupter in the insurance industry. In the same way that fintech companies have disrupted the traditional banking sector, reimagining financial platforms for a new generation.

My client has developed a flexible insurance that is a mobile-first, frictionless platform which lets people interact with their insurance provider with the same ease, speed and transparency they’re already used to having with providers in other sectors. Customers can pay monthly, instantly make changes to their cover, and bring all their disclosure, payment and claims information together in a single place.

This is a fantastic opportunity for you to build something special with a close knit team, we offer lots of progression in a fast paced position where two days are never the same!

Responsibilities:

Develop and sustain an efficient data pipeline architecture that can adapt to the needs of the organisation.
Compile extensive, intricate datasets that align with both functional and non-functional business objectives.
Devise and execute enhancements to internal workflows by automating manual tasks, refining data distribution methods, and redesigning infrastructure to improve scalability.
Construct the necessary framework for effective data extraction, transformation, and loading (ETL), leveraging SQL and AWS-based ''big data'' technologies.
Develop analytics solutions that draw from the data pipeline, offering actionable insights into areas like customer acquisition, operational efficacy, and other vital business performance indicators.
Collaborate with software engineers, database architects, data analysts, and data scientists to drive data-centric projects and ensure a streamlined data delivery architecture.
Innovate and automate data and reporting infrastructures for more effective data management.
Assist our data scientists in transitioning machine learning and data science algorithms from the experimental stage to scalable production deployments.
Implement data governance best practices, ensuring data security, quality, and compliance with relevant regulations.
Constantly monitor the data pipelines and architecture, making improvements to enhance performance and reduce costs where possible.
Stay abreast of new technologies and tools in the data engineering space to maintain the relevancy and efficiency of our data systems.

Qualifications:

4+ years of experience in a Data Engineer role.
Must have lots of AWS experience (Essential)
Experience building and optimising ‘big data’ data pipelines, architectures and data sets.
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
Strong analytic skills related to working with unstructured datasets and ability to build processes supporting data transformation, data structures, metadata, dependency and workload management.
A successful history of manipulating, processing and extracting value from large disconnected datasets.
Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.

You should also have experience using the following software/tools:

AWS Services: Deep understanding of AWS services like S3, Redshift, EMR, Kinesis, and Glue, used for data storage and processing.
ETL Processes: Experience with Extract, Transform, and Load (ETL) processes and tools, particularly in an AWS environment using services like AWS Glue or Data Pipeline.
Big Data Technologies: Proficiency in big data technologies like Hadoop and Spark, and how they integrate with AWS services like EMR.
Programming Languages: Strong programming skills in languages commonly used in data engineering such as Python, Java, or Scala.
SQL and NoSQL Databases: String proficiency in SQL for querying relational databases like Amazon RDS, and experience with NoSQL databases like DynamoDB.
Data Modeling: Ability to design and implement data models in data warehousing solutions like Amazon Redshift.
Streaming Data: Experience with real-time data processing using AWS services like Kinesis or managed Kafka.
Data Security: Understanding of data encryption, IAM roles, and other security best practices within AWS.
DevOps: Familiarity with DevOps practices including CI/CD, and tools like Terraform, Cludformation, AWS CodeBuild, CodeDeploy, and CodePipeline.
APIs: Knowledge of RESTful API interactions, especially within the AWS ecosystem.
Experience supporting and working with cross-functional teams in a dynamic environment.
Strong problem-solving skills, with the ability to troubleshoot and address technical challenges.
Excellent communication skills, with the ability to work in a team and convey technical concepts clearly.

When you apply for this role a consultant from Urban Empire Recruitment will give you a call if you’re successful.

Please note due to the large volume of applications we receive for these roles, if we have not contacted you within 7 days then unfortunately your application hasn''t been successful. however, we may contact you regarding other roles. We''re sorry we can''t contact you directly, but we wish you all the best in your job search.

Job Type: Full-time

Salary: £75,000.00-£85,000.00 per year

Benefits:

Free flu jabs
Health & wellbeing programme
Private dental insurance
Private medical insurance
Work from home

Schedule:

Monday to Friday

Ability to commute/relocate:

London: reliably commute or plan to relocate before starting work (required)

Application question(s):

Do you have a deep understanding of AWS services like S3, Redshift, EMR, Kinesis, and Glue, used for data storage and processing?
Please note we do NOT provide sponsorship or Visa with this position.

Experience:

Data engineering: 5 years (preferred)

Work authorisation:

United Kingdom (required)

Work Location: In person