Senior Azure Data Engineer (Databricks)

Atrium (EMEA); Dublin; On-site; EUR 90,000 - 120,000; Full time

Job summary

Atrium (EMEA) in Dublin seeks a hands-on Senior Azure Data Engineer to design, build and maintain scalable data pipelines using Databricks (PySpark) and Azure Data Lake. You will work on event-based streaming ingestion and optimize Spark workloads, collaborating with leads and peers to deliver robust data solutions.

The role requires 6–9 years in data engineering, strong SQL and Python, and a pragmatic, delivery-oriented mindset to ensure quality and timely delivery in a production environment.

Qualifications

• 6–9 years of experience in data engineering roles.
• Hands-on experience with PySpark, SQL and Python.
• Experience building and optimizing data pipelines on Azure.
• Strong understanding of ETL/ELT best practices and data modeling.

Responsibilities

• Design, build, and maintain scalable data pipelines using Azure Databricks (PySpark) and Azure Data Lake.
• Implement event-based or streaming ingestion pipelines (Event Hub, Kafka, etc.).
• Develop reliable ETL/ELT workflows with data quality and performance in mind.
• Optimize Spark workloads for simplicity, efficiency, and maintainability.
• Collaborate with leads to review designs and improve engineering practices.
• Participate in peer code reviews and troubleshoot production issues.

Skills

PySpark

SQL

Python

Azure Databricks

Azure Data Lake

ETL/ELT

Data pipelines

Streaming

ADF

Kafka

Event Hub

Orchestration tools

Tools

ADF

Kafka

Event Hub

Job description

Hands-on Senior Azure Data Engineer (Databricks) with 6–9 years’ experience building scalable data pipelines and streaming solutions using Databricks, PySpark and Azure Data Lake. Strong in SQL, Python and ETL/ELT, with a focus on simplicity, quality and delivery.

Role Overview:

• Location: Dublin
• Contract Type: 12 months

JOB SUMMARY:

• We are seeking a Senior Data Engineer to join our data engineering team. This is a hands‑on delivery role focused on building, optimizing, and maintaining scalable data pipelines using the Azure data platform.
• The ideal candidate is pragmatic, delivery-oriented, and collaborative, someone who can design fit‑for‑purpose solutions, work closely with leads and peers, and contribute positively to team culture.

Required Experience & Skills

• 6–9 years of experience in data engineering roles.

Strong hands-on experience with:

• PySpark
• ADF / orchestration tools
• Solid programming experience in SQL and python.
• Good understanding of ETL/ELT best practices, data modeling, and distributed data processing.
• Experience working in production‑grade data platforms.
• Strong communication skills and a collaborative, professional working style.
• Ability to take feedback positively and adapt solutions to team standards.

KEY RESPONSIBILITIES:

• Design, build, and maintain scalable data pipelines using Azure Databricks (PySpark) and Azure Data Lake.
• Hands on implementation experience in event‑based or streaming ingestion pipelines (Event Hub, Kafka, etc.).
• Develop reliable ETL/ELT workflows, ensuring data quality, performance, and operational stability.
• Optimize Spark workloads with a focus on simplicity, efficiency, and maintainability.
• Work closely with the Data Engineering Lead to implement agreed designs, review solutions, and continuously improve engineering practices.
• Participate in peer code reviews, applying best practices and constructive feedback.
• Troubleshoot production issues proactively and support operational excellence.
• Collaborate effectively with cross‑functional teams across Ireland and the US, communicating clearly and professionally.