Data Engineer: Scale Lakehouse & Mentor (Hybrid)

Arm Limited; Cambridge; Hybrid; GBP 50,000 - 70,000; Full time

Job summary

A leading technology company in Cambridge is seeking a Data Engineer to join their Productivity Engineering group. The role involves building scalable data processing systems and collaborating with engineering teams worldwide. Ideal candidates will have experience in programming languages such as Python and Scala, alongside a strong background in modern data technologies. This is an opportunity to contribute to critical projects in a dynamic environment.

Benefits

Strong team culture

Learning opportunities

Emphasis on diversity and inclusion

Career conversations

Qualifications

• Degree and/or equivalent experience in engineering, computer science or a related data-intensive field.
• Proficient with one or more programming languages (Python, Scala).
• Hands-on experience with modern data technologies, like Databricks and Spark.
• Comfortable building ETL/ELT workflows using orchestration frameworks.
• Excellent written and verbal communication skills.

Responsibilities

• Build scalable, fault-tolerant distributed data processing systems.
• Participate in architectural discussions and product roadmap.
• Partner with engineering for new data flows focusing on performance.
• Ensure data quality and compliance across all stages.
• Mentor and provide technical leadership to team members.

Skills

Python

Scala

Data quality management

Data governance

Communication skills

ETL/ELT workflows

Education

Degree in engineering, computer science or related field

Tools

Databricks

Spark

Kafka

Elasticsearch

AWS

GCP

Azure

Job description

A leading technology company in Cambridge is seeking a Data Engineer to join their Productivity Engineering group. The role involves building scalable data processing systems and collaborating with engineering teams worldwide. Ideal candidates will have experience in programming languages such as Python and Scala, alongside a strong background in modern data technologies. This is an opportunity to contribute to critical projects in a dynamic environment.