Senior Engineer, Data Engineering

4 weeks ago

South East London, United Kingdom Canada Life Full time

Location: London, Potters Bar, Bristol or Isle of Man (Hybrid working options available)
The Data Engineer is a technical role responsible for designing, developing, and maintaining data pipelines within the IT department. The pipelines will be realised in a modern lake environment and the engineer will collaborate in cross-functional teams to gather requirements and develop the conceptual data models. This role plays a crucial part in driving data-driven decision-making across the organisation, ensuring data availability, quality, and accessibility for various business needs.
Data Pipeline Development

Design, model, develop and maintain data pipelines to ingest, store, process, and present data.
Ensure data quality, accuracy, and consistency.
Collaborate with data architects to ensure data pipelines align with the overall data architecture strategy.
Data Transformation and Integration

Perform data transformation tasks, including data cleansing, enrichment, and aggregation, to prepare data for analytics and reporting.
Integrate data from structured and unstructured sources, ensuring compatibility and alignment with data models and business requirements.
Automate data transformation processes to improve efficiency.
Data Quality Assurance

Implement and maintain data quality checks and validation processes to identify and resolve data anomalies and errors.
Monitor data pipelines for data quality issues and implement data quality improvements.
Collaborate with business stakeholders to define data quality requirements.
Data Modelling and Schema Design

Collaborate with data architects and data scientists to design and implement data models, schemas, and structures.
Ensure that data models support business reporting and analytics needs while optimizing query performance.
Maintain data dictionaries and metadata to document data structures and relationships.
Performance Optimization

Optimize data storage, retrieval, and query performance by implementing indexing, partitioning, and caching strategies.
Monitor data processing performance and address bottlenecks as they arise.
Stay updated with best practices in data processing performance tuning.
Create and maintain documentation for data pipelines, data transformation processes, and data integration procedures.
Foster a culture of knowledge sharing within the data engineering team and across the organization.
Collaborate effectively with cross-functional teams, data stakeholders, and business units to understand data requirements and deliver data solutions that meet business needs.
Communicate technical concepts and data solutions to non-technical stakeholders in a clear and understandable manner.
Commercial experience of DataBricks, SQL, Python, Power BI
Experience in data engineering, including designing and developing data pipelines for retrieval / ingestion / presentation / semantics in an Azure environment.
Effective communication and collaboration skills to work with cross-functional teams and gather data requirements.
Skills in data modelling (both structured and unstructured data)
Data optimisation for performance, scalability, and efficiency.
Experience in a financial corporation

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