Senior Data Engineer - Databricks & Lakehouse (Hybrid)

Hometrack; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Benefits offered by this job

25 days annual leave

Volunteer day

Digital detox day

Cycle to work

Calm App membership

Enhanced parental leave

Fertility treatment support

Group income protection

Private medical insurance

Gym on-site / regional gym access

Pension 7.5%

Bonus up to 10%

Referral bonus up to £5K

Job summary

Hometrack is seeking a Senior Data Engineer to join our Data Services product team in London. You will help deliver data platforms and datasets powering our market-leading AVM, serving mortgage lenders, builders and utilities alike.

The role emphasizes scalable data products, collaboration, and robust data governance. Hybrid working with 2 days per week in the London Bridge office; you will write maintainable code, review peers, and optimize ETL and data pipelines to ensure accuracy,

Qualifications

• Experience with modern data platforms and data lake architectures.
• Proven ability to design and optimize ETL pipelines for performance and reliability.
• Strong proficiency in Python and PySpark, with SQL fluency.

Responsibilities

• Own data engineering outcomes for Hometrack's Data Services initiatives.
• Build and optimize data pipelines and datasets powering AVM and analytics.
• Collaborate with Product, Analytics, Security and Software teams to simplify complex data problems.

Skills

Databricks

Delta Lake

Lakehouse

ETL

Python

SQL

PySpark

Data pipelines

Data products

Collaboration

Tools

Databricks

Delta Lake

Lakehouse

Job description

Hometrack is seeking a Senior Data Engineer to join our Data Services product team in London. You will help deliver data platforms and datasets powering our market-leading AVM, serving mortgage lenders, builders and utilities alike.

The role emphasizes scalable data products, collaboration, and robust data governance. Hybrid working with 2 days per week in the London Bridge office; you will write maintainable code, review peers, and optimize ETL and data pipelines to ensure accuracy,