Data Engineer

Confidential Company; Dublin; Hybrid; EUR 90,000 - 120,000; Full time

Job summary

Confidential Company is seeking a Data Engineer to design, build and maintain scalable data pipelines and data warehouse solutions. You will collaborate with senior data engineers, architects and product owners to ensure high-quality data assets.

The role is hybrid, three days onsite per week, offering opportunities to work across AWS/Azure/GCP environments and modern data tooling. Strong communication and problem-solving skills are essential.

Qualifications

• Minimum of 5 years in Data Engineering or related field.
• Minimum of 3 years hands-on Databricks in production.
• Strong expertise in cloud platforms (AWS/Azure/GCP) and Data Lake/Data Warehousing.
• Experience with ETL tools and BI solutions (Airflow, PowerBI).
• Experience with data quality and governance tools (Atlan, Monte Carlo).
• Solid knowledge of data modelling concepts.
• Excellent communication and collaboration skills.
• Problem-solving and analytical mindset.
• Ability to work autonomously and as part of a team.

Responsibilities

• Design, build and maintain scalable Databricks data pipelines to ingest, transform and deliver high-quality data into Data Lake and Data Warehouse environments.
• Develop and optimise ETL/ELT workflows using Airflow to ensure reliable data delivery.
• Manage and enhance cloud-based data platforms (AWS/Azure/GCP), focusing on performance, scalability, security and cost efficiency.
• Implement and maintain data quality, governance, lineage and monitoring frameworks with Atlan and Monte Carlo.
• Partner with business stakeholders, BI teams and engineering teams to design data models and deliver analytics-ready datasets.

Skills

Communication skills

Collaboration

Analytical mindset

Problem solving

Autonomy

Education

Master's in Computer Science / Data Science or related field

Tools

Databricks

Airflow

PowerBI

Atlan

Monte Carlo

AWS

Azure

GCP

Job description

The Data Engineer is a highly skilled data management specialist in charge of developing and implementing complex data pipelines and data warehouse solutions. They will work closely with senior data engineers, architects and product owners to ensure high-quality delivery of Data Assets.

Please note that this is a hybrid role, three days per week onsite.

Required Experience:

• At least 5 years of experience in Data Engineering or a related field
• A minimum of 3 years of hands-on experience with Databricks in a production environment
• Strong expertise in cloud platforms (e.g. AWS, Azure, GCP), Data Lake technologies and Data Warehousing
• Experience with data ETL tools and BI solutions (e.g., Airflow, PowerBI)
• Experience with data quality and governance tools (e.g., Atlan, Monte Carlo)
• Solid knowledge of data modelling concepts
• Excellent communication and collaboration skills
• A problem-solving and analytical mindset
• Ability to work autonomously and as part of a team

Key responsibilities & duties include:

• Design, build and maintain scalable Databricks data pipelines to ingest, transform and deliver high-quality data into Data Lake and Data Warehouse environments
• Develop and optimise ETL/ELT workflows and orchestration processes using tools such as Airflow to ensure reliable and automated data delivery
• Manage and enhance cloud-based data platforms (AWS / Azure / GCP), focusing on performance, scalability, security and cost efficiency
• Implement and maintain data quality, governance, lineage and monitoring frameworks using tools such as Atlan and Monte Carlo to ensure trusted and compliant data
• Partner with business stakeholders, BI teams and engineering teams to design data models and deliver analytics-ready datasets that support reporting and decision-making

Desirable Experience:

• Master's in Computer Science, Data Science or a related field
• Proven experience in designing, developing and implementing complex data pipelines and data warehouse solutions in an enterprise environment
• Experience with Scaled Agile planning and execution