Data Analyst - Senior Mongo & GCP

***** Please do not apply if you don't have commercial experience with ***** 1: MongoDB 2: Python 3: Google Cloud Platform / Big Query NOTE: We are not after a person who does reporting and analytics, its a different skill. We need a person that does ETL, cleans data, matches data, fixes bad data - we need a data person. BEFORE YOU APPLY - YOU MUST UNDERSTAND: MAPBOX, OSM and Address or spacial data - this will be part of the interview. DO NOT APPLY IF YOU DON'T UNDERSTAND THIS We are seeking a highly experienced Senior Data Expert to join our team and lead the design, management, and optimisation of complex data systems. This role requires deep hands-on expertise in MongoDB, Google Cloud Platform (GCP), address data schemas, and GIS/spatial data. You will play a key role in building and maintaining scalable data solutions, improving data quality, and supporting products that rely on accurate property, location, and address-based intelligence. Key Responsibilities: Design, manage, and optimise large-scale datasets within MongoDB Build and maintain data pipelines and workflows within Google Cloud Platform (GCP) Work with complex address data schemas, including validation, matching, normalisation, and enrichment Develop and manage GIS/spatial data processes, including geospatial analysis and mapping-related datasets Improve data quality, integrity, and performance across multiple data sources Support the ingestion, transformation, and integration of structured and unstructured data Collaborate with product, engineering, and business teams to deliver accurate, scalable data solutions Troubleshoot schema, performance, and data consistency issues Assist in designing systems for property, location, and spatial intelligence use cases Required Skills and Experience Minimum 10 years of commercial experience in data engineering, data architecture, or related senior data roles Strong commercial experience with MongoDB Strong working knowledge of Google Cloud Platform (GCP), including relevant data services Deep understanding of address data structures and schemas Experience working with GIS, geospatial datasets, coordinates, boundaries, and spatial relationships Strong experience in data modelling, ETL/ELT processes, and large dataset handling Strong Python and/or SQL skills for data processing and automation Experience with data cleansing, deduplication, and record matching Ability to work with high-volume, complex datasets with a strong focus on accuracy, performance, and scalability Assessment Process Candidates must be able to clearly demonstrate their technical capability throughout the recruitment process. This may include: A technical interview Practical problem-solving discussion Demonstration of relevant past commercial work or project experience Please do not apply unless you can confidently demonstrate strong hands-on technical skills in interview. Highly Regarded Experience with property, real estate, government, or location-based datasets Experience with geocoding, spatial joins, and address matching Familiarity with tools such as BigQuery, Cloud Storage, Dataflow, or related GCP services Understanding of Australian address datasets such as G-NAF or similar frameworks Experience supporting map-based or spatial intelligence products What We’re Looking For: A highly analytical and detail-oriented senior data professional Someone who can work independently and solve complex technical problems A candidate who understands that clean, structured, and spatially accurate data drives product value A team player who can bridge deep technical expertise with practical business outcomes