Location: Dublin 2
Other locations: Primary Location Only
Requisition ID: 1726387
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Your Key Responsibilities:
We are seeking an experienced Data Engineer with a strong background in supporting business and analytics teams in Financial Services industry by designing, developing, and operating robust data pipelines. The ideal candidate will have experience in working with Azure Cloud and proficiency in using Microsoft Azure Data Services and platforms such as Azure SQL, Data Warehouse, Data Factory, Data Lakes, HDInsight, and Stream Analytics. Core Azure SQL, MSSQL server.
They will also have understanding of the underlying data flow architectures, will have supported finance, operations, privacy & security, compliance & regulatory projects in the past, have a functional understanding of the data sets used in the relevant business domain(s) they supported, as well be adept at data sourcing, data wrangling, issue gap and root cause analysis, ETL and implementing data solutions for effective process change and improvement strategies. Experience is agile software delivery is a must.
- Design, implement, and manage robust and scalable data pipelines and solutions for core systems and applications.
- Collaborate with IT and business teams to understand business and technical requirements in order to identify, prioritise and document data requirements for management and business insights.
- Design, build, and maintain data solutions that transform raw data into structured formats suitable for analytics.
- Develop and manage data models and ETL processes to ensure effective and efficient data ingestion and transformation.
- Analyse and conduct gap analysis in existing data architectures to identify impact areas and design solution options.
- Conduct thorough analysis of existing data processes and systems, identifying areas for improvement. Work closely with Data Stakeholders (e.g. Product and System Owners, Technical Leads, Business and Change Leads, Data and Solution Architects) to communicate and influence implementation of the identified technical enhancements.
- Lead performance optimisation identification of data pipeline bottlenecks and areas for improvement. Optimise query performance in data storage solutions and implement best practices for data processes and transformations to enhance the efficiency of ETL workflows.
- Implement security measures to protect sensitive data throughout the data lifecycle, including encryption, access controls, and data masking.
- Ensure compliance with data governance policies and regulatory requirements, such as GDPR, BCBS239, IFRS9, IRB or HIPAA.
- Monitor data quality and integrity throughout the transformation process, implementing controls and fixes as needed and maintaining compliance with the organisation’s Data Governance and Data Management policies and procedures.
- Design data architecture that can scale horizontally and vertically to accommodate growing data volumes and user demands.
- Support the design and implementation of integrated technology solutions with data expertise, ensuring alignment with business goals and compliance with internal and external policies, procedures, and regulations.
- Design and implement robust reporting frameworks that facilitate timely and accurate financial status reporting