We are seeking a highly skilled and motivated Senior-Staff Data/Geospatial Engineer to join our dynamic team. In this role, you will play a pivotal role in the transformation and management of geospatial data, ensuring its accuracy, availability, and usability for a variety of applications. You will collaborate closely with cross-functional teams to develop data models, optimize spatial operations, and contribute to the development of customer-facing APIs.
- Minimum Qualification: Degree
- Experience Level: Senior level
- Experience Length: 5 years
A bit about you
Bachelor's or Master's degree in Computer Science, Geospatial Science, or related field.
Proven experience in geospatial data management and transformation.
Strong background in data engineering, including data lake and pipeline management (5+ years).
Proficiency in databases such as Postgres and PostGIS.
Exceptional knowledge of data modeling and spatial concepts.
Experience in spatial optimization and customer-facing API development is advantageous.
Excellent problem-solving skills and a keen attention to detail.
Effective communication and team management skills.
About your role at Ready
Geospatial Data Modeling:
Collaborate closely with the frontend team, product team, and geospatial data scientist to understand the challenge and provide data modeling solutions.
Ensure data models are adaptable to evolving project needs and future scalability.
Design and optimize database schemas to support spatial-temporal queries and analyses.
Implement data indexing and partitioning strategies for improved query performance.
Data Transformation and Ingestion:
Execute data transformation processes to convert raw geospatial data into structured formats.
Orchestrate the data transformation and ingestion workflow with Airflow.
Set up scheduled data transformation and ingestion jobs for scalability.
Data Storage and Maintenance:
Implement and maintain data lake and data warehouse architecture for efficient storage and retrieval of geospatial data.
Design different strategies for optimizing the spatial-temporal data storage, update, and backup.
Design and implement best practice with cloud solutions: AWS and GCP.
Spatial Data Expertise:
Apply expertise in static tiling, dynamic tiling, and raster tiles to optimize the retrieval and rendering of geospatial data.
Maintain the tileserver for performance and reliability.
Implement spatial indexing and caching strategies to accelerate spatial data access.
Develop automated data verification pipelines to validate the quality and consistency of geospatial datasets.
Leverage statistic and data visualization tools to validate the data or identify data abnormalities.
Implement data cleansing and transformation routines to correct errors and inconsistencies.
Monitor data verification processes and promptly address issues to maintain data reliability.
Utilize SQL and Python to perform data manipulation, transformation, and analysis tasks.
Develop custom scripts and functions to automate geospatial data processing workflows.
Develop custom packages for data engineer team to share.
Stay updated on the latest updates in cloud SQL and Python for data engineering.
Customer-Facing API Development:
Contribute to the development of customer-facing APIs that expose geospatial data and services.
Ensure API endpoints are well-documented, secure, and efficient in data retrieval and delivery.
Collaborate with frontend developers to integrate APIs seamlessly into applications.
Machine Learning, Optimization and AI - From Solution to Production:
Collaborate with domain experts to understand specific spatial challenges and devise effective solutions.
Solve complex spatial optimization problems, such as route planning and network planning, to enhance geospatial capabilities.
Work on integrating machine learning or AI frameworks into production environments to leverage geospatial data.
Collaborate with data scientists and AI engineers to deploy models that enhance geospatial capabilities.
Ensure the scalability and reliability of AI-driven solutions for geospatial applications.
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