Data Engineer

The role focuses on scalable data pipelines, spatial analytics, and map centric applications that support business decisions and sustainable urban and environmental initiatives while ensuring robust day operations without travel requirements. Drive continuous improvement initiatives by evaluating emerging geospatial tools frameworks and cloud capabilities and recommending practical enhancements to existing data and analytics solutions.

Our client, a IT Services and Consulting company, is looking for a Data Engineer for their Charlotte, NC/Hybrid location.
 
Responsibilities:

• The Data Engineer will design, build, and optimize cloud based geospatial data solutions using AWS, PySpark, and Python in a hybrid work model.
• The role focuses on scalable data pipelines, spatial analytics, and map centric applications that support business decisions and sustainable urban and environmental initiatives while ensuring robust day operations without travel requirements.
• Design and implement scalable geospatial data pipelines on AWS that ingest, transform, and store complex spatial datasets to enable reliable analytics for internal and external stakeholders.
• Develop and maintain high performing PySpark based data workflows that process large volumes of location intelligence data and deliver accurate outputs for mapping and decision support platforms.
• Create efficient Python modules and reusable libraries that handle spatial computations, coordinate transformations, and geospatial business rules to streamline development across project teams.
• Configure and manage AWS services for data storage computation and orchestration to ensure secure resilient and cost efficient hosting of geospatial solutions in a hybrid work environment.
• Collaborate with data scientists and domain experts to translate business requirements into map driven analytical models that generate insights for transportation urban planning and environmental monitoring use cases.
• Optimize geospatial queries and spatial indexing strategies to improve performance of interactive maps dashboards and APIs that are consumed by diverse enterprise applications. Implement rigorous data quality checks and validation routines on spatial datasets to ensure accuracy consistency and trust in geocoding routing and proximity analyses used across the organization.
• Document end to end data flows technical designs and operational procedures so that geospatial platforms are easy to maintain extend and onboard for new projects and teammates. Integrate external geospatial data sources including satellite imagery open data and partner feeds into AWS based repositories to broaden analytical coverage and improve societal impact assessments.
• Support day shift operations by monitoring data jobs resolving pipeline issues and coordinating with cross functional teams to minimize downtime and maintain reliable access to mapping services.
• Drive continuous improvement initiatives by evaluating emerging geospatial tools frameworks and cloud capabilities and recommending practical enhancements to existing data and analytics solutions.
• Ensure that all geospatial engineering work aligns with company standards for security privacy and compliance to protect sensitive location information and maintain public and client trust.
• Contribute to organizational purpose by enabling evidence based planning and resource optimization through accurate location intelligence ultimately supporting more sustainable and inclusive communities.

 
Requirements:

• Experience: 7 to 11 Yrs
• Required skills:  Python, PySpark, AWS
• Demonstrate strong proficiency in AWS data and compute services with hands on experience designing and operating production grade solutions for geospatial workloads.
• Apply advanced PySpark skills to build distributed data processing jobs including performance tuning and efficient handling of large scale spatial data structures.
• Use solid Python programming expertise to craft clean maintainable and well tested codebases that support complex geospatial logic and integration tasks.
• Bring a deep understanding of geospatial concepts such as projections vector and raster data spatial joins and topology to design robust analytical solutions.
• Show practical experience with hybrid work models including effective remote collaboration and onsite coordination for project delivery and stakeholder engagement.
• Exhibit strong problem solving abilities and analytical thinking to troubleshoot data issues optimize pipelines and improve the accuracy of location based insights.
• Leverage clear communication and documentation skills to work with multidisciplinary teams and present technical findings in accessible and actionable terms for business partners.

 
Why Should You Apply?

• Health Benefits
• Referral Program
• Excellent growth and advancement opportunities