Data Scientist / Data Engineer
- Financial Services Organization
Our company is a leading Financial Services organization, focused on wealth management, that believes team work should drive the company's innovation.
Role Overview
Join our small IT team of experts, and step into a pivotal role where your expertise will shape the future of data-driven decision-making.
As a data engineer/scientist you'll be at the forefront of turning client data into a valuable asset in order to facilitate ambitious business growth and to influence strategic direction, collaborating with a team that values innovation and celebrates achievement.
You will also be critical in harnessing the power of Artificial Intelligence in order to enhance business insights and operational capabilities.
This is your opportunity to make a tangible impact, elevate your existing skills, and contribute to a culture that champions growth and inspires excellence. Embrace a dynamic environment where your ideas are not only welcomed but drive real change, and where each day brings new challenges and exciting opportunities for professional and personal development.
Key Responsibilities include:
Data Pipeline Development:
Design, build, and maintain scalable and efficient data pipelines using Snowflake and Azure Data Services (e.g., Azure Data Factory, Azure Synapse).
Data Engineering:
Develop and optimise ETL/ELT processes, ensuring data quality, integrity, and security across all stages of the data lifecycle.
Advanced Analytics & AI:
Apply statistical analysis, machine learning, and AI techniques to extract actionable insights and solve complex business problems.
Solution Design:
Collaborate with business representatives and Data Architect to assist in formulating technical designs from business requirements.
Key Technical Skills & Experience
You must have at least 3 to 5 years recent experience in a similar role as a Data Engineer or Data Scientist, preferably in the Financial Services sector.
You must have strong expertise in Snowflake and Azure Data Services, as well as ETL and large-scale data management.
Technical Expertise includes:
* Proven experience with Snowflake (data warehousing, SQL, performance tuning).
* Experience in applying AI and machine learning frameworks.
* Strong proficiency in Azure Data Services (Data Factory, Synapse, Databricks, etc.).
* Advanced programming skills in Python and SQL.
* Familiarity with CI/CD pipelines and DevOps practices for data solutions.
* Data Engineering:
Solid understanding of data modelling, ETL/ELT processes, and data integration.
Experience with large-scale data processing and distributed computing.
* Analytics & AI:
Ability to design and implement advanced analytics solutions.
Experience with feature engineering, model deployment, and monitoring.
* Cloud Platforms:
Hands-on experience with cloud-based data architectures, especially Azure.
* Soft Skills:
Strong problem-solving, analytical, and communication skills.
Ability to work independently and as part of a cross-functional team.
Desirable
· Strong experience with **Azure Data Factory** and **Snowflake** for data integration
· Experience with cloud-based data platforms (Azure, AWS, Snowflake).
· Knowledge of financial services products, processes, and regulatory requirements.
· Familiarity with agile project management and process improvement methodologies.
Must be eligible to work in Ireland with no visa restrictions.