Data Engineer: Build Scalable ETL Pipelines & Models

Disguise Technologies Ltd; Greater London; Híbrido; GBP 65 000 - 90 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Unlimited PTO

Hybrid work

Mental health support

Gig allowance

Belonging policies

Training & mentoring

Resumo da oferta

Disguise Technologies Ltd in London seeks an experienced Data Engineer to design, build, and maintain robust data pipelines and a scalable data warehouse. You will work with large, complex datasets to empower analysts and stakeholders to make data-driven decisions shaping the company’s future.

Key responsibilities include ETL/ELT pipeline development, data modelling, and data quality monitoring. Strong SQL, Python and AWS experience, plus CI/CD and Docker, are required to thrive in our

Qualificações

• 3+ years hands-on data engineering experience.
• Strong SQL and Python proficiency.
• Experience with AWS services including Batch, Lambda, Glue, ECR, RDS, Redshift, S3.
• Knowledge of data warehousing, star/snowflake schemas, and data modelling.
• Proficient with Git/GitHub and CI/CD pipelines.
• Familiarity with containerisation (Docker).
• Ability to work independently and in a team.
• Experience with data visualisation tools like Power BI.

Responsabilidades

• Design, build, and maintain ETL/ELT data pipelines.
• Develop data models and schemas in our data warehouse.
• Integrate data from APIs, internal DBs, and streaming platforms.
• Monitor data quality and ensure accurate production data.
• Collaborate with analysts and engineers to meet data requirements.
• Improve performance of data architecture and pipelines.
• Share best practices and foster knowledge sharing.

Conhecimentos

SQL

Python

AWS

GIT / GitHub

CI/CD

Power BI

Docker

CloudFormation

Ferramentas

AWS Lambda

AWS Glue

AWS Redshift

S3

GitHub Actions

Docker

CloudFormation

Descrição da oferta de emprego

Disguise Technologies Ltd in London seeks an experienced Data Engineer to design, build, and maintain robust data pipelines and a scalable data warehouse. You will work with large, complex datasets to empower analysts and stakeholders to make data-driven decisions shaping the company’s future.

Key responsibilities include ETL/ELT pipeline development, data modelling, and data quality monitoring. Strong SQL, Python and AWS experience, plus CI/CD and Docker, are required to thrive in our