Data Engineer

Confidential Company; Dublin; Hybrid; EUR 90,000 - 130,000; Full time

Job summary

Confidential Company in Ireland is seeking a Data Engineer to design, build and maintain scalable Databricks data pipelines feeding Data Lake and Data Warehouse environments. You will collaborate with senior data engineers, architects and product owners to ensure trusted data assets.

This is a hybrid role: three days on-site per week in County Dublin. The candidate has strong cloud experience (AWS/Azure/GCP), ETL/ELT orchestration with Airflow, and data quality governance skills to drive

Qualifications

• 5+ years of experience in Data Engineering or a related field
• 3+ years of hands-on experience with Databricks in a production environment
• Strong expertise in cloud platforms (AWS, Azure, GCP), Data Lake technologies and Data Warehousing
• Experience with data 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
• A problem-solving and analytical mindset
• Ability to work autonomously and as part of a team
• 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

Responsibilities

• Design, build and maintain Databricks data pipelines to ingest, transform and deliver data to Data Lake/Data Warehouse
• Develop and optimise ETL/ELT workflows and orchestration using Airflow
• Manage and enhance cloud-based data platforms focusing on performance, scalability, security and cost efficiency
• Implement and maintain data quality, governance, lineage and monitoring frameworks using Atlan and Monte Carlo
• Partner with stakeholders, BI teams and engineering to design data models and deliver analytics-ready datasets

Skills

Communication

Collaboration

Analytical thinking

Problem solving

Autonomy

Teamwork

Education

Master's degree in Computer Science, Data Science or related field

Tools

Databricks

Airflow

PowerBI

Atlan

Monte Monte Carlo

AWS

Azure

GCP

ETL/ELT tooling

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
• 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
• 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