Data Scientist

Data Scientist

Fulltime - Permanent position

Hybrid 2/3 days onsite based in South Dublin.

Our High Profile Client seeks Data Scientist for their team.

Role Overview

• As a data engineer 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

• 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.
• Performance Optimisation:

Monitorand tune data systems for performance, scalability, and cost- effectiveness.

• Collaboration &Communication:

Work closely with data analysts and business teams to deliver data-driven solutions and communicate findings effectively.

• Documentation & Best Practices:

Maintain comprehensive documentation and promote best practices in data engineering, analytics, and AI.

Key Technical Skills & Experience

Technical Expertise:

• 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, ETL, and large-scale data management is strongly preferred.
• 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.