AWS Data Engineer

🔒 Confidential Employer
Posted 9 November 2024
LOCATION
UK
TYPE
Contract
LEVEL
Mid-Senior level
CATEGORY
Data Engineering
This employer holds a UK Home Office sponsor license — sponsorship for this specific role is at the employer’s discretion

SKILLS

Python SQL Data Modelling ETL (SQL/Python/PySpark) AWS Data Stack (Glue, Lambda, S3, Athena) Redshift Terraform PostgreSQL Apache Spark Data Streaming Applications Middleware (e.g., Kafka, Rabbitmq)

FULL DESCRIPTION

AWS Data Engineer
Job ID: 151775

Type: Contract /permanent

Experience: Fresehers and 0+2 years

No. of Positions: 1

Travel Required: Yes

Location: UK

Who we are

[Employer hidden — view at passion-project.co.uk] is one of the competitive consulting companies, headquartered in United Kingdom that provide cutting-edge technology solutions, that enable businesses to thrive in the digital era. We specialize in Cloud, DevOps, Data Science, Blockchain, IoT, and Metaverse technologies, and our team of experts is dedicated to delivering innovative solutions that drive business growth and transformation.

Our team of experts has years of experience in above technologies. They are highly skilled, use the latest tools and technologies to design, develop, and implement solutions that transform businesses and drive innovation.

What will your job look like

Help build and integrate the next gen data platform
Analyse and aggregate data into new data models for use by the rest of the company
Write complex ETL in SQL/Python/PySpark to generate reports from a variety of sources.
Make sure that data is secure, reliable and easily accessible across the company by leveraging the latest technologies
Build tools for automation, monitoring and alerting of the data pipelines.
Write Infrastructure as Code using Terraform
Collaborate in design and problem-solving sessions.
Suggest improvements and introduce best practices into the team
Requirements

This is a mid/senior level role with strong skills in Python, SQL and data-modelling
Good experience developing, architecting and scaling data services
Strong ownership and self-drive from the first line of code to the impact on the end user. If you like autonomy and being in the drivers seat, we would love to have you in our team!
Strong product mindset and a good ability to understand product context and develop success metrics
Redshift, Glue, S3, Athena,Step Function, Lambda, SQL/Python/PySpark, Tableau / Power BI
Previous experience introducing best practices or processes into a team and a strong desire to help others succeed
Good architectural design skills and being able to discuss the merits and trade-offs of using any particular design approach and technologies
Bonus: Experienced working in a AWS Data Stack (AWS Glue, Lambda, S3, Athena)
Bonus: Experienced using PostgreSQL
Bonus: Experienced using Apache Spark for data processing
Bonus: Experienced with data streaming applications middleware (e.g., Kafka, Rabbitmq)
Bonus: Experienced using Terraform for Infrastructure as code
Experience in Redshift database query optimization for better performance, manage large tables partitions
Must have experience working with AWS tools and services (Glue, EMR, Athena, Step Function)
Data Pipelining skills Data blending using python and SQL
Develop & support ETL pipelines
Develop data models that are optimized for business understand-ability and usability
Develop and optimize data tables using best practices for partitioning, compression, parallelization, etc.
Develop and maintain metadata, data catalogue, and documentation for internal business customers
Help internal business customers troubleshoot and optimize SQL and ETL solutions to solve reporting problems
Work with internal business customers and partner technical teams to gather and document requirements for data publishing and consumption
Experience in Documentation create technical specifications and able to translate existing technical designs into data transformation
Visualisation experience Tableau / Power BI
Development/Delivery methodologies Agile Scrum DevOps

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