GCP Data Engineer
Posted
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:
Requirements:
Why Should You Apply?
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
- Category Name Required Importance Experience
- Analytics Python Yes 1
- Data Management BigQuery Yes 1
Why Should You Apply?
- Health Benefits
- Referral Program
- Excellent growth and advancement opportunities
