Python Data Engineer – Geospatial Pipelines & ETL

Brave; Cirencester; On-site; GBP 48,000 - 72,000; Full time

Benefits offered by this job

Pension Scheme

Healthcare Assistance Scheme

Birthday Off

Cycle to Work Scheme

Social Events

Additional 3 days holiday during shut/

Job summary

Landstack is a UK land and planning intelligence platform based in Cirencester. We are seeking a Python data engineer to own ingestion pipelines for planning data, enabling fast, reliable processing and delivery to customers.

You will build ETL pipelines, design data models in PostgreSQL/PostGIS, and optimize OpenSearch indexing. The role emphasizes data quality, monitoring, and thorough documentation within a collaborative engineering team.

Qualifications

• 3–5 years of professional Python experience, focused on data processing.
• Strong SQL and PostgreSQL experience; PostGIS a plus.
• Experience with ETL/pipeline patterns: batch jobs, queues.
• Familiar with pandas or polars and handling large datasets.
• Experience with AWS services and Docker/Kubernetes.
• Commitment to data quality and correctness.

Responsibilities

• Build and maintain Python ingestion pipelines for planning and geospatial data.
• Design data models and transformations for spatial data in PostgreSQL/PostGIS.
• Build and tune bulk indexing into OpenSearch.
• Add monitoring, validation and data-quality checks.
• Profile and optimise long-running batch jobs on AWS.
• Document sources, schemas and pipeline behaviour.

Skills

Python

SQL

ETL pipelines

Pandas/Polars

AWS & Docker/Kubernetes

Data quality

Tools

PostgreSQL

PostGIS

OpenSearch

Redis

SQS

Docker

Kubernetes

S3

Job description

Landstack is a UK land and planning intelligence platform based in Cirencester. We are seeking a Python data engineer to own ingestion pipelines for planning data, enabling fast, reliable processing and delivery to customers.

You will build ETL pipelines, design data models in PostgreSQL/PostGIS, and optimize OpenSearch indexing. The role emphasizes data quality, monitoring, and thorough documentation within a collaborative engineering team.