Avance Consulting
DataOps Engineer
Manchester
Posted about 15 hours ago
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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.
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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.
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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.
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Skills
Data Engineering
AWS
SQL
Python
PySpark
Scala
Terraform
Git
CI/CD
Data Pipeline Design
Data Quality Assurance
Troubleshooting
Monitoring
Collaboration
Agile
Machine Learning