Data Engineer - Level 2

Cpl Group; Dublin; Hybrid; EUR 92,000 - 120,000; Full time

Job summary

Cpl Group is seeking a Data Engineer II in Dublin on a hybrid, long-term contract basis. You will design, build, and maintain data pipelines, optimize ETL processes, and collaborate with cross-functional teams across global client engagements.

The role emphasizes scalable data solutions, data quality, and rapid delivery in multi-client projects. Candidates should have strong SQL skills, experience with Databricks and Spark, and a background in data modeling and relational databases.

Qualifications

• Experience with data engineering concepts including data modeling and scalable data solutions.
• Strong SQL skills for querying, optimizing, and analyzing large datasets.
• Experience with Databricks and Spark in a data engineering context.
• Familiarity with version control and data validation practices.

Responsibilities

• Design, implement, and maintain enterprise ETL processes for data platforms.
• Collaborate with Data Engineers and Analysts to deliver high-value data solutions.
• Develop scalable data pipelines and optimize data processing workflows.
• Translate business questions into data requirements and deliver actionable insights.
• Apply industry best practices like version control, code reviews, and testing.

Skills

Data modeling

SQL optimization

Cross-functional collaboration

Problem solving

Multi-project management

Communication

Education

Bachelor's degree in a quantitative field

Tools

Databricks

Spark

Microsoft SQL Server

GitHub Copilot

Job description

Data Engineer

• Dublin – Hybrid
• Long Term Contract
• Daily Rate

Data Engineer level II to contribute to the data management aspects of client engagements for Test & Learn and other Services products. In this role, you will develop robust data pipelines, implement scalable data solutions, and collaborate with cross-functional teams. Engineers work in small, flexible teams. Every team member contributes to designing, building, and testing features.

The role:

• Support the design, implementation, and maintenance of enterprise ETL processes for data platforms, for a global client base.
• Assist in the data delivery process, working alongside Data Engineers and Analysts to support on-time, accurate, high-value, and robust data solutions across multiple clients and industry sectors.
• Use SQL and other database technologies to optimize data processing. Develop scalable and efficient code to reduce the time required to handle large data sets.
• Partner with analytics and business stakeholders to understand business questions and translate them into data requirements.
• Learn and apply industry best practices, such as version control, code reviews, and data validation, to ensure quality in data processes.
• Participate in efforts to design streamlined processes to automate routine data tasks.
• Build trust-based working relationships with peers and clients across local and global teams. Collaborate with senior and peer engineers on multiple projects in parallel.

All About You:

• Experience as a Data Engineer or in a similar role, with a strong understanding of data engineering concepts and methodologies, including data modeling and database design to support scalable data solutions.
• Strong knowledge of writing and optimizing SQL queries to retrieve, manipulate, and analyze data efficiently.
• Experience with Microsoft SQL Server and relational databases.
• Ability to design, implement, and maintain ETL pipelines.
• Experience with Databricks and Spark
• Experience with productivity tools such as GitHub Copilot
• Ability to innovate, think critically, and break down problems.
• Ability to handle tasks on multiple projects and navigate competing priorities.
• Ability to analyze and troubleshoot data issues and provide solutions with minimal supervision.
• Basic knowledge of testing and validating data to ensure accuracy and consistency in data pipelines.
• Excellent verbal and written communication skills, with the ability to articulate complex ideas clearly and concisely to both technical and non-technical stakeholders.
• Bachelor's degree in a quantitative discipline such as Engineering, Mathematics, Finance, Business, or a related field. Equivalent practical experience may also be considered.