Data Engineer

AWS Limited
Leeds, UK
24 days ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Amazon Web Services Amazon S3 Data Analysis Continuous Integration Data as a Services Data Validation Information Engineering Data Governance Data Integration Extract Transform Load (ETL) Data Transformation
+23 more
Data Migration Data Warehousing Dimensional Modeling Github Monitoring of Systems Python (Programming Language) Enterprise Messaging Systems SQL Databases Data Streaming Data Ingestion Sql Optimization Change Data Capture Cloudformation Data Layers Build Management Data Lakes Deployment Automation Data Management Cloudwatch Terraform Splunk Data Pipelines GXP

Job description

Data Engineer We are looking for an experienced Data Engineer to join a major data transformation programme on an initial 3-month contract. This is a hands-on role for someone who enjoys building robust, scalable data platforms and pipelines. You will work as part of a wider technical delivery team, helping to develop a modern AWS-based data environment that supports enterprise reporting, analytics and operational decision-making. The successful candidate will ideally be able to attend the Leeds office one day per week. However, flexible arrangements can be discussed for the right person. The role You will play a key part in designing, building and improving cloud-based data solutions. This will include developing data pipelines, integrating data from multiple systems and helping to create trusted, well-governed datasets for reporting and analytics. You will work closely with Data Architects, Analysts, Developers and other technical stakeholders to turn business and technical requirements into practical, scalable solutions. Key responsibilities Design and build scalable data lake and data warehouse solutions on AWS. Develop data ingestion, transformation and storage pipelines to support reporting, analytics and operational use cases. Work with AWS services including S3, Redshift, Glue, Lambda, Lake Formation, Athena and EventBridge. Implement Bronze, Silver and Gold data layers using Medallion Architecture principles. Build and maintain ETL/ELT pipelines across batch, streaming and Change Data Capture (CDC) workloads. Develop reusable transformation frameworks, data models and curated datasets using Python, SQL and dbt. Support data migration and integration activity across a range of source and target systems. Build integrations using APIs, messaging technologies and file-based ingestion methods. Implement data validation, reconciliation and error-handling processes to improve data quality. Support data governance, lineage, security and audit requirements.

Requirements

Help automate deployments and infrastructure using Terraform or CloudFormation. Contribute to CI/CD pipelines using GitHub Actions or similar tooling. Improve monitoring and operational support using tools such as CloudWatch and Splunk. Produce clear technical documentation for pipelines, mappings, transformations and data flows. Promote good engineering practice, automation, standardisation and continuous improvement. About you You will be a capable, delivery-focused Data Engineer with experience working on modern cloud data platforms. You should be comfortable working independently, but equally happy collaborating with a multidisciplinary technical team. You will have strong experience with AWS data services and be confident designing and developing data pipelines in complex transformation, migration or integration environments. Key skills and experience Proven experience designing and delivering AWS-based data platforms. Strong hands-on experience with services such as S3, Redshift, Glue, Lambda, Lake Formation, Athena and EventBridge. Experience implementing Medallion Architecture, including Bronze, Silver and Gold data layers. Strong data engineering experience across batch, streaming and CDC ingestion patterns. Advanced SQL skills and strong Python development experience. Experience using dbt for data transformation and modelling would be highly beneficial. Experience building and optimising ETL/ELT pipelines. Good understanding of data warehousing, dimensional modelling and analytical data structures. Experience with data integration, APIs, messaging and file-based data ingestion. Knowledge of Terraform or CloudFormation for Infrastructure as Code. Experience with CI/CD tooling, ideally GitHub Actions. Experience with monitoring, observability and data quality frameworks. Knowledge of CloudWatch, Splunk or similar monitoring tools. An understanding of data governance, lineage, validation and security principles. Strong communication skills and the ability to work with both technical and non-technical stakeholders.This is a fast-moving requirement, and we are keen to identify suitable candidates quickly. Please get in touch with relevant profiles

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