À propos
Our client, a IT Services and Consulting company, is looking for a GCP Data Engineer for their Preferred to work in any CVS locations. Remote working is also fine location. Responsibilities:
Serve as a senior geospatial data analyst responsible for designing, implementing, and optimizing data pipelines on cloud platforms to support map based analytics and decision making. Apply expertise in streaming and batch processing, large scale query optimization, and advanced scripting to deliver reliable insights that drive business value in a hybrid day shift environment. Design robust geospatial data ingestion pipelines using GCP Dataflow to reliably process high volume spatial and temporal datasets for mapping and analytics use cases. Develop and optimize complex analytical queries in GCP BigQuery to transform raw geospatial data into curated datasets and dashboards that support critical business decisions. Build and maintain Kafka based streaming solutions that capture real time location events and sensor feeds to keep map based products accurate and timely. Implement scalable PySpark data transformations that clean, enrich, and aggregate large geospatial datasets while maintaining high performance and data quality. Create Python3 based automation scripts that orchestrate data workflows, perform advanced spatial analysis, and generate repeatable analytical outputs for stakeholders. Configure and monitor cloud resources to ensure stable, secure, and cost efficient operation of geospatial data pipelines across development and production environments. Conduct detailed spatial analysis and exploratory data profiling to uncover patterns, anomalies, and trends that inform product enhancements and operational strategies. Document data models, processing logic, and geospatial business rules in a clear and structured manner to support maintainability, auditability, and effective knowledge sharing. Collaborate with product teams, data consumers, and domain experts to refine requirements and translate complex geospatial needs into implementable technical solutions. Validate data quality using automated checks and reproducible tests to ensure that geospatial outputs are accurate, complete, and aligned with defined standards. Optimize query performance and storage design in BigQuery by tuning partitioning, clustering, and schema definitions for large geospatial tables. Provide support for incident analysis and root cause investigation related to data pipeline failures or data quality issues, and drive sustainable corrective actions. Share best practices for geospatial analytics, cloud data engineering, and coding standards to improve team productivity and solution reliability. Requirements:
Experience: 6to10Yrs Showcase professional experience of six to ten years in data engineering or analytics with significant focus on geospatial processing and cloud native solutions. Demonstrate advanced hands on proficiency in GCP Dataflow including design of streaming and batch pipelines for complex spatial and temporal data sources. Exhibit strong expertise in GCP BigQuery covering data modeling, performance tuning, geospatial functions, and cost optimized query design. Apply proven knowledge of Kafka including topic design, consumer group configuration, and integration with Dataflow to support real time data scenarios. Use solid Python3 programming capabilities to build modular, testable, and reusable components that implement geospatial analytics and automation. Leverage practical experience with PySpark to process large scale datasets and integrate spatial libraries that enhance analytical capabilities. Display familiarity with general geospatial concepts including coordinate systems, map projections, and spatial joins to correctly interpret and transform data. Utilize effective communication and stakeholder engagement skills to explain analytical findings, data constraints, and solution tradeoffs to diverse audiences. Employ sound problem solving abilities and attention to detail to troubleshoot complex data issues and design resilient cloud based data solutions. Years of Experience: 10.00 Years of Experience Why Should You Apply?
Health Benefits Referral Program Excellent growth and advancement opportunities
Compétences linguistiques
- English
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