Software Engineer

About the role

Hire Hangar is actively searching for a Software Engineer to join their graph-database-backed social listening platform. In this role, you will own the end-to-end pipeline that transforms raw social signals into actionable relationship insights. You will be responsible for designing and maintaining backend services that model complex connections in graph databases while also building intuitive front-end visualizations. A significant portion of your work will involve developing and optimizing web scraping and crawler infrastructure to ensure continuous, high-quality data ingestion. You will need to collaborate closely with product and data teams to translate ambiguous requirements into scalable technical solutions. The position requires troubleshooting performance bottlenecks across the entire stack, from ingestion through storage to visualization rendering. Early-stage engineering pace and evolving priorities are expected, so comfort with ambiguity and rapid iteration is essential. US work authorization without sponsorship is required for this position.

Key facts

What you'll do

• Design, build, and maintain backend services that model and query complex relationships in graph databases such as Neo4j, TigerGraph, Dgraph, ArangoDB, Amazon Neptune, or similar systems using Cypher or Gremlin query languages.
• Develop and maintain robust real-time ingestion pipelines capable of handling high-throughput social and web data streams with low latency and high reliability.
• Build, operate, and continuously optimize web scraping and crawler infrastructure to ensure comprehensive and efficient data collection from diverse online sources.
• Develop responsive and interactive front-end features and dashboards that clearly and performantly visualize network relationships, leveraging modern visualization techniques.
• Collaborate cross-functionally with product managers, data scientists, and other engineers to translate business requirements into scalable technical implementations.
• Write clean, maintainable, well-tested code across the full stack, ensuring consistency and quality in both backend services and frontend applications.
• Troubleshoot and resolve performance bottlenecks across ingestion, storage, and visualization layers to ensure optimal system behavior.
• Participate in architectural decision-making and contribute to the evolution of graph data models and visualization strategies.
• Implement monitoring and alerting for critical components to enable proactive identification and resolution of issues.
• Mentor junior engineers and contribute to technical documentation to improve team-wide knowledge and code quality.

Requirements

• Hands-on experience with graph databases including Neo4j, TigerGraph, Dgraph, ArangoDB, Amazon Neptune, or similar platforms, and proficiency in graph query languages such as Cypher or Gremlin.
• Demonstrated experience with real-time or streaming infrastructure technologies such as Kafka, Kinesis, Flink, or Spark for processing high-volume data streams.
• Strong programming proficiency in at least one backend language including Python, Go, or Node.js/TypeScript for building scalable services.
• Solid front-end development experience with modern frameworks and libraries such as React, Next.js, and TypeScript for creating interactive user interfaces.
• Practical experience designing and maintaining data pipelines, ETL processes, and web scraping or crawler infrastructure at scale.
• Proven ability to thrive in high-growth early-stage engineering environments where priorities evolve rapidly and ambiguity is common.
• Authorization to work in the United States without the need for sponsorship, as this is a non-negotiable requirement for the role.
• Strong problem-solving skills and the ability to debug complex systems across multiple layers including networking, storage, and application code.
• Excellent written and verbal communication skills for effective collaboration with cross-functional teams.
• A commitment to writing clean, efficient, and well-documented code that adheres to best practices and engineering standards.

Nice to have

• Hands-on experience with graph and network visualization libraries such as D3, Cytoscape, Sigma.js, vis.js, or Recharts for building compelling network diagrams.
• Prior work on social listening platforms, social media data systems, or large-scale web data processing platforms.
• Familiarity with search and analytics technologies such as Elasticsearch, OpenSearch, Redis, or workflow orchestration tools like Airflow.
• Experience working at seed to Series B stage startups where roles are diverse and impact is immediate.
• Practical experience with cloud platforms including AWS or GCP, and containerization technologies such as Docker and Kubernetes for deployment and scaling.

Practical notes

This is a contract position with US EST-PST time zone expectations. Applicants must have current US work authorization without sponsorship, as this is a hard requirement stated in the posting. The role involves significant time working remotely with potential engagement in Columbia, Maryland, depending on operational needs. Follow the live posting if location or compensation details change, as these elements are subject to updates. Employer claims regarding company stage, awards, or recognition should be treated as contextual information rather than independently verified facts. Application process requirements such as specific instructions or required video submissions, if stated in the original posting, are binding for candidates moving forward. When evaluating fit, prioritize the must-have requirements over the nice-to-have items to ensure alignment with the position's core demands. Remember that graph systems combined with streaming pipelines and visualization create a full-stack systems challenge, and weaknesses in any layer can manifest as slow or incorrect network views. Crawler reliability is foundational because downstream processes depend entirely on consistent and high-quality data ingestion. Visualization performance directly impacts the product promise, as slow or unresponsive network diagrams can degrade user experience and trust. Preferred technologies such as D3-class visualization libraries become critical when network diagrams serve as the primary user interface. US work authorization without sponsorship remains a strict filter that disqualifies candidates unable to meet this criterion.