DataOps Engineer

Role Title: DataOps Engineer Location: Manchester, UK - Hybrid Work setup: 2 days onsite/week Job Type: Contract Role Description: Key Responsibilities Data Engineering & Delivery • Design develop and test data engineering solutions aligned to business requirements and quality standards. • Build and support end-to-end data pipelines covering ingestion transformation and consumption layers. • Apply engineering best practices to ensure scalability reliability and performance of data solutions. DataOps & Automation • Drive automation-first approaches across data pipelines and operational processes reducing manual intervention. • Identify opportunities to improve process maturity tooling and operational efficiency. Cloud & Infrastructure • Develop and manage cloud-based data platform components using infrastructure-as-code techniques (e.g. Terraform). • Deploy and maintain services within AWS-based data ecosystems (e.g. S3 Glue Redshift). CI/CD & Engineering Practices • Contribute to CI/CD pipelines ensuring reliable and repeatable deployments. • Follow and enhance Git-based version control and release management practices. Monitoring Support & Troubleshooting • Investigate and resolve data pipeline failures performance issues and data quality concerns. • Use monitoring and logging tools to identify and address operational issues. • Provide support for production systems including occasional out-of-hours support where required. Governance Assurance & Quality • Ensure adherence to engineering standards security controls and approved design principles. • Participate in peer reviews testing and assurance activities to maintain solution quality. • Identify risks issues and defects and escalate where appropriate. Collaboration & Stakeholder Engagement • Work effectively with cross-functional teams and third-party suppliers to deliver solutions. • Communicate clearly with both technical and non-technical stakeholders. • Support and mentor team members where required. Skills & Experience Essential • Strong experience in data engineering development within a commercial environment. • Hands-on experience with AWS data services including S3, Glue and Redshift (or comparable cloud technologies). • Strong programming capability in SQL, Python, PySpark or Scala. • Proven experience using Terraform for infrastructure as code and Git for version control. • Experience with CI/CD pipelines and deployment workflows. • Strong understanding of data pipeline design and implementation. • Experience in data quality assurance and testing within pipelines. • Demonstrated ability to troubleshoot and resolve technical issues in production environments. Desirable • Experience with tools such as Databricks Informatica Qlik Replicate/Compose SAS or SSIS. • Knowledge of data modelling methodologies (e.g. Kimball Data Vault Lakehouse). • Experience in financial services data environments. • Exposure to Agile delivery methodologies. • Experience industrialising or supporting machine learning models. Qualifications • Degree in a relevant discipline or equivalent experience in data engineering or software engineering. • Professional certifications in cloud platforms or DevOps practices are advantageous. Key Capabilities & Behaviours • Strong focus on quality governance and engineering best practices. • Automation-first mindset with the ability to improve process maturity and efficiency. • Ability to articulate technical solutions design decisions and pipeline flows clearly. • Proactive approach to continuous improvement and learning. • Ability to work collaboratively and influence within a cross-functional delivery environment.