Data Manager - Data Quality & Governance
Location: Manchester - Hybrid, 2 days per week onsite
Contract: Contract
Focus: Data Quality, Data Governance, Data Observability, SQL, Python, and Financial Data
*Urgent 6 Month Contract*
This is a *Manchester, UK* based role with an excellent *immediate start* within a *Global Technology Client* that is working on *Implementing and maintaining data-quality standards, controls and validation processes across enterprise datasets*.
We are looking for a hands-on *Data Manager/Data Quality specialist* to join a major enterprise technology environment in Manchester.
This role sits at the intersection of *data management, engineering and the business*, with responsibility for ensuring critical data is accurate, reliable, observable and appropriately governed throughout its life cycle.
You will work closely with Data Managers, Engineering Managers, Data Engineers and business stakeholders to establish data-quality controls, understand how data moves between systems, monitor the health of critical datasets and translate technical data issues into clear business impact.
The position is particularly suited to someone with strong experience across *Data Quality, Data Governance and Data Observability*, combined with practical SQL and Python skills.
Key Responsibilities
- Implement and maintain *data-quality standards, controls and validation processes* across enterprise datasets.
- Define and monitor data-quality requirements covering accuracy, completeness, consistency, validity and timeliness.
- Develop validation solutions to check *data values, schemas and data integrity*.
- Use *SQL and Python* to interrogate datasets, identify quality issues, automate checks and support data validation.
- Build and maintain *data-quality dashboards and data-observability solutions*.
- Monitor data pipelines and critical datasets to identify failures, anomalies and availability issues.
- Support monitoring of relevant *SLIs and SLOs* and help ensure data solutions meet agreed service expectations.
- Implement monitoring and failure-detection mechanisms to ensure data remains available and timely.
- Support *Data Governance* processes including data quality monitoring, data lineage, logical data models and data ownership.
- Map data flows and dependencies between systems and business processes.
- Support the creation and maintenance of *logical and physical data models*.
- Connect and reconcile datasets from different systems to provide consistent and trusted information.
- Work with engineering teams responsible for data ingestion, batch processing and event-based data flows.
- Work with financial and ledger-based datasets, ensuring appropriate controls, traceability and reconciliation.
- Translate complex technical data issues into clear language for business and non-technical stakeholders.
- Work autonomously while collaborating closely with Data Management and Engineering leadership.
- Use modern tooling, including *AI-assisted development/validation tools*, where appropriate to improve the efficiency and quality of technical work.
Essential Experience
We are looking for candidates who can demonstrate strong practical experience in:
- Data Quality and Data Management
- Data Governance
- Data Observability
- Data-quality monitoring and dashboards
- Data validation and reconciliation
- Data lineage and data flows
- SQL
- Python or similar Scripting/data manipulation tools
- Relational and/or dimensional data modelling
- Working with enterprise datasets across multiple systems
- Monitoring, failure detection and data availability
- Working collaboratively with Data Engineering and technology teams
- Translating technical concepts and data issues into meaningful business language
Financial Data Experience
Experience working with *financial, accounting or ledger-based data* would be particularly valuable.
- General ledger or financial datasets
- Financial data reconciliation
- Finance data controls
- Transactional data
- ERP data
- Financial reporting datasets
- Data lineage across finance systems
The Person
We are looking for someone who is technically credible but equally comfortable working with the business.
You should be able to move between discussions with Data Engineers and Engineering Managers and conversations with business stakeholders, explaining *what a data problem is, why it matters and what needs to happen to resolve it*.
You will need to be comfortable working independently, taking ownership of problems and driving them through to resolution rather than waiting for detailed instruction.
This is *not purely a Data Engineering position*. Candidates whose experience is primarily focused on building cloud infrastructure and pipelines without meaningful Data Quality, Governance or Observability experience are unlikely to be the right fit.
Likewise, this is not a purely policy-focused Data Governance position. The role requires someone who can work *hands-on with data using SQL, Python, validation, monitoring and observability techniques*.
Key Skills:
- Data Manager
- Data Quality
- Data Governance
- Data Observability
- SQL
- Python
- Data Validation
- Data Lineage
- Data Modelling
- Data Quality Dashboards
- Data Management
- Financial Data
- Ledger Data
- Data Reconciliation
- Data Monitoring
- SLIs
- SLOs
- DAMA
- DMBOK
- SAP
- S/4HANA
- Manchester.