Blue Coding

Data Engineer

• Design, develop, and maintain data pipelines and datastores that support enterprise analytics, data science, and operational workloads.
• Lead and support large-scale database migration initiatives, including on-premises to cloud migrations.
• Monitor, analyze, and optimize the performance and stability of data layer services and platforms.
• Ensure data integrity, quality, and compliance across pipelines and datasets.
• Collaborate closely with peers across engineering, analytics, and technology teams.
• Guide, coach, and mentor data engineers, BI developers, and analysts.
• Design and implement enterprise-scale data solutions with long-term business impact.
• Build and maintain data processing solutions using Python and/or Scala.
• Work with a variety of data ingestion patterns, including SFTP, APIs, streaming, and batch processing.
• Design and support database models optimized for analytical and reporting use cases.
• Implement monitoring, alerting, and observability for data pipelines and infrastructure.
• Maintain clear and comprehensive documentation of data architectures, pipelines, and processes.
• Work within an Agile environment, collaborating through tools such as Jira and Git.

Senior Data Engineer – V

• Design & implement a modern data warehouse using Amazon Redshift, ensuring scalability and performance.
• Develop and maintain ETL pipelines using AWS Glue (Python/PySpark), moving data from SQL Server (RDS) and other sources.
• Structure our S3 data lake for efficient storage, partitioning, and integration with Redshift.
• Define data models (star schema, dimensional modeling) to support reporting and analytics.
• Establish data governance—documentation, quality checks, and monitoring for pipelines.
• Collaborate with BI teams to ensure the warehouse meets reporting needs (CRM, dashboards).
• Optimize costs by tuning Redshift clusters, managing Glue job efficiency, and automating workflows.
• Troubleshoot data infrastructure issues and optimize performance across systems.
• Contribute to the long-term vision for the data platform, including new tools, workflows, and process automation.
• Maintain documentation of data systems, flows, and integration strategies.
• Support project planning and estimation in coordination with business and technical teams

Senior Data Engineer, VM

Product Marketing

• Define and lead the comprehensive global strategy for the client's platform and all associated modular offerings.
• Establish the client's platform as a leader in the e-commerce platform solutions space.
• Serve as the internal authority on market trends, competitive landscapes, and analyst relations.
• Present strategies, market performance, and competitive intelligence to the executive leadership team and board of directors.
• Develop high-impact sales tools, including presentations, demos, case studies, ROI calculators, and training materials.
• Direct the creation of all core marketing assets, including website copy, solution briefs, white papers, analyst reports, and press releases.
• Maintain a deep understanding of the client's platform, architecture, features, and roadmaps.
• Act as the primary liaison between Product Management, Sales, Marketing, and Customer Success to ensure consistent messaging and successful execution of GTM plans across the organization.
• Mentor and potentially manage junior product marketing resources as the team scales around the client's platform.

Executive Product Marketer – WSM

Machine Learning Engineer

• Design, build, and deploy machine learning models in production environments
• Develop classification systems to automatically categorize educational content by subject, grade level, and learning standards
• Build and maintain computer vision pipelines (e.g., object detection, OCR, image segmentation) for worksheet and student-submission analysis
• Design and implement RAG (Retrieval-Augmented Generation) systems using large content libraries
• Engineer and optimize prompts for AI-generated educational content and assessment validation
• Build AI-driven quality assurance systems to evaluate generated content against educational taxonomies
• Develop agentic AI workflows that iteratively refine and improve generated outputs
• Deploy and operate AI services on AWS, ensuring scalability, reliability, and cost efficiency
• Collaborate directly with client stakeholders and cross-functional engineering teams
• Define and, when required, contribute to data labeling or feedback strategies supporting model quality
• Maintain clear documentation for models, pipelines, and AI system behavior
• Participate in code reviews and promote AI engineering best practices

Senior AI / ML Engineer

Frontend Engineer

• Build and maintain API-driven backend services using Django and Django Rest Framework, supporting scalable and data-intensive workflows.
• Design and optimize complex ORM queries to power reporting, analytics, and aggregated data views.
• Develop background and asynchronous processing for batch operations such as data processing and report generation.
• Apply caching strategies to improve performance on high-traffic or data-heavy endpoints.
• Manage database schema evolution through migrations as product features expand.
• Build and maintain interactive, responsive frontend components using React and modern hooks.
• Implement efficient data-fetching and caching patterns to support complex UI workflows.
• Make pragmatic UI/UX decisions while collaborating closely with engineering and product stakeholders.
• Own features end-to-end, from design and implementation through testing and deployment.
• Contribute through code reviews, shared standards, and occasional mentorship.
• Balance new feature development with ongoing refactoring and quality improvements.
• Work effectively in a low-process, high-trust environment that values autonomy, accountability, and strong engineering judgment.

Senior Full-stack Engineer – Django/React

Analyst

• Own the creation, execution, and maintenance of manual test cases based on functional and technical requirements.
• Validate end-to-end campaign and tracking workflows, including user interactions, lead capture flows, and data attribution mechanisms.
• Analyze campaign and analytics metrics to identify tracking gaps, configuration errors, or data inconsistencies.
• Test both UI behavior and data-layer implementations, ensuring alignment between tracked events and reported metrics.
• Log, track, and manage defects in Jira, providing clear reproduction steps and validation of fixes.
• Maintain and update structured test cases in TestRail, ensuring visibility and auditability of test coverage.
• Collaborate daily with Engineering, Advertising Operations, and QA leadership within an Agile environment.
• Identify areas where test automation could add value, contributing to long-term quality strategy discussions.

Testing Analyst

Full-stack Engineer

• Build and maintain full-stack web applications using React, Node.js, and modern JavaScript frameworks.
• Develop features that extract, normalize, and present large communication datasets in a clear and reliable manner.
• Implement backend services and desktop applications in Node.js to process, encrypt, validate, and export data efficiently.
• Design frontend flows in React that guide non-technical users through complex, multi-step workflows.
• Ensure data consistency and reliability across web and mobile ingestion sources.
• Investigate and parse large datasets and tables to support new data sources and export formats.
• Strengthen authentication, authorization, logging, and auditability to meet security and compliance standards.
• Automate validation and testing of data exports to prevent downstream errors.
• Troubleshoot production issues by analyzing logs, reproducing edge cases, and delivering verified fixes.
• Collaborate closely with engineering and cross-functional stakeholders to scope, prioritize, and ship improvements continuously.