Lead Data Engineer: Real-Time Pipelines & Offshore Team

henryschein; Dublin; On-site; EUR 120,000 - 180,000; Full time

Job summary

Henry Schein is seeking a highly technical Senior Data Engineer to design, build, and optimize scalable data pipelines and lakehouse platforms. You will lead a small offshore data engineering team and coordinate delivery of high‑quality data solutions.

The role requires hands‑on implementation, strong Python/Scala and SQL skills, and experience with Databricks/Spark, cloud platforms (Azure preferred), and data governance.

Qualifications

• 8-12 years of data engineering experience and hands-on coding.
• Proven track record coordinating offshore or distributed teams.
• Strong Python/Scala, SQL, and data pipeline optimization skills.
• Cloud data platforms experience, Azure preferred.

Responsibilities

• Design, develop, and optimize batch and real-time data pipelines using Databricks and Spark.
• Build scalable lakehouse architectures and high‑performance data models.
• Provide technical leadership and coordiante offshore delivery teams.
• Define tasks, review deliverables, and ensure timelines and standards.
• Lead ETL/ELT framework implementations and reusable patterns.
• Troubleshoot performance, data skew, partitioning, and large-scale processing.
• Implement data quality, lineage, observability, and governance controls.
• Collaborate with API, Analytics, and Platform teams to deliver production‑grade data assets.
• Promote best practices in coding, testing, and CI/CD for data pipelines.

Skills

Python

Scala

SQL

Data modeling

Performance tuning

Leadership

Tools

Databricks

Spark

Kafka/Confluent

Snowflake

Azure

Job description

Henry Schein is seeking a highly technical Senior Data Engineer to design, build, and optimize scalable data pipelines and lakehouse platforms. You will lead a small offshore data engineering team and coordinate delivery of high‑quality data solutions.

The role requires hands‑on implementation, strong Python/Scala and SQL skills, and experience with Databricks/Spark, cloud platforms (Azure preferred), and data governance.