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Data Engineer Python Spark ETL

Client Server Ltd.
Posted a day ago, valid for 4 days
Location

London, Greater London EC1R 0WX

Salary

£40,000 - £48,000 per annum

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Contract type

Full Time

In order to submit this application, a Reed account will be created for you. As such, in addition to applying for this job, you will be signed up to all Reed’s services as part of the process. By submitting this application, you agree to Reed’s Terms and Conditions and acknowledge that your personal data will be transferred to Reed and processed by them in accordance with their Privacy Policy.

Sonic Summary

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  • The position is for a Data Engineer (Python Spark ETL) based in London with a salary of up to £90k.
  • The role involves building a new Data Lake from scratch using modern tools, primarily Python and Spark, in an AWS environment.
  • Candidates should have experience in Data Lakes, Data Warehousing, and ETL processes, along with strong Python and SQL skills.
  • The company offers a hybrid work-from-home policy, requiring three days in the London office per week.
  • Applicants should have a minimum of 3-5 years of relevant experience in data engineering.

Data Engineer (Python Spark ETL) London / WFH to £90k

Are you a tech savvy Data Engineer keen to make an impact, delivering Greenfield systems?

You could be progressing your career at a successful and growing Cyber Security Risk Management tech company that specialises in solutions for SME's, working on complex and interesting systems at the cutting edge of technology. The company is scaling and enjoying great success.

As a Data Engineer you'll be instrumental in building and scaling the data infrastructure to support advanced data aggregation, storage and analytics capabilities as the company enters a phase of data maturity, holding data from hundreds of thousands of organisations since they were established seven years ago. You'll take ownership of building a new Data Lake from scratch using a range of modern tools and technologies, primarily Python and Spark in an AWS environment.

This is an impactful role where you'll be at the heart of the technology function to drive optimisations and develop new capabilities that maximise the value of the company's accumulated data sets.

Location / WFH:

There's a hybrid work from home policy with three days in the London office per week.

About you:

  • You are an experienced Data Engineer with a strong knowledge of Data Lakes, Data Warehousing, ETL / ELT processes and data pipeline orchestration
  • You have strong Python and SQL coding skills
  • You have experience with big data frameworks and tools including Spark
  • You have a good knowledge of AWS data services (e.g. S3, Redshift, EMR, Glue)
  • You have strong analytical, problem solving and critical thinking skills
  • You have excellent communication skills and experience of working across teams

What's in it for you:

As a Data Engineer (Python Spark ETL) you will earn a competitive salary plus benefits including:

  • Salary to £90k
  • Private Medical Healthcare including Dental and Vision cover
  • Pension
  • Share Option scheme
  • Employee Wellness Programme
  • Summer time hours
  • £2k personalised training budget

Apply now to find out more about this Data Engineer (Python Spark ETL) opportunity.

At Client Server we believe in a diverse workplace that allows people to play to their strengths and continually learn. We're an equal opportunities employer whose people come from all walks of life and will never discriminate based on race, colour, religion, sex, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. The clients we work with share our values.

Apply now in a few quick clicks

In order to submit this application, a Reed account will be created for you. As such, in addition to applying for this job, you will be signed up to all Reed’s services as part of the process. By submitting this application, you agree to Reed’s Terms and Conditions and acknowledge that your personal data will be transferred to Reed and processed by them in accordance with their Privacy Policy.