As a Data Engineer, you will be instrumental in extracting and transforming data from various source systems, integrating different sources to create datasets for insight generation and advanced analytics. You will strive for efficiency by aligning data systems with business goals and work to make raw data more useful to the organization.
Responsibilities:
- Support project teams in designing, building, testing, and implementing ETL processes to make data consumable for analytics, coordinating with peer group on engineering activities and reviewing outputs for quality.
- Support the development and testing of data engineering solutions ensuring that solutions balance functional and non-functional requirements
- Perform data validation and verification to ensure data accuracy, completeness, and consistency across source and target systems. Identify and report any discrepancies or issues.
- Perform regression, integration and performance testing for data workflows.
- Follow leadership within your own team for the workgroup, ensuring appropriate project delivery frameworks are in place.
- Liaise with peers across both `Build' and `Run' engineering teams to define and deliver analytics solutions that provide business value.
- Aid in the resolution of complex data quality issues, leveraging technical expertise and driving continuous improvement.
- Help to keep process documentation up to date for better cross-team knowledge transfer.
- Stay abreast of the latest Engineering industry trends; looking for opportunities to implement these in your day-to-day work and provide suggestions for PTSB best-practice.
- Support the D&A Community of Practice and leverage other training and learning settings for your professional development and career enhancement.
- Provide support and mentoring/coaching to less experienced colleagues.
Requirements:
Essential
- Proven data engineering experience with know-how in enterprise class data engineering platforms e.g. Teradata Vantage, Snowflake etc
- Degree in Actuarial Science, Behavioural Economics, Computer Science, Mathematics, Economics, Engineering, IT or relevant field.
- Experience with pipeline creation, data provisioning & storage, sandbox provisioning, architecture, unstructured data, ETL development, data modelling, big data, APIs, Python, SQL, NO-SQL databases, and big data tools.
- Experience contributing to research activities.
- Capabilities in Service Management, Data Engineering, and Enterprise Support.
- Experience with Teradata EDW data warehousing, ETL processes, and data modelling
- Familiarity with big data technologies (Hadoop, Spark, etc.)
- Familiarity with cloud-based data platforms (AWS, Azure, etc.)
- Familiarity with CORA, JIRA, Confluence
This is a Permanent (hybrid) position based in Dublin/Cork, the Republic of Ireland.
Is this you?
Please apply online on our website or via the apply link of this role. Your application will be sent through to our Talent Acquisition team and they will be in touch regarding your application.
We reserve the right to draw up a shortlist for interview.
The Bank understands the importance of a consistent and relentless focus on championing diversity and inclusion. We aim to attract, recruit, and retain individuals with diverse backgrounds, skills, competencies and abilities to work collaboratively to enhance the service we provide to all of our customers and the communities we serve.