Application Guide

How to Apply for Senior Software Engineer, Data Platform

at Hayden AI

🏢 About Hayden AI

Hayden AI develops AI-driven solutions specifically for urban transit safety and sustainability, focusing on real-world impact in cities. Their work directly addresses modern urban challenges like traffic flow and public safety through technology, making it appealing for engineers who want to see their work affect daily life. The company's focus on both transit efficiency and environmental sustainability offers a mission-driven environment beyond typical tech roles.

About This Role

This Senior Software Engineer role involves evolving Hayden AI's data platform using AWS services to handle streaming, batch, and analytical workloads at scale for transit data. You'll design robust data pipelines and enforce data quality standards, directly impacting the reliability of AI models that inform urban transit decisions. Your work ensures the data foundation for safer, faster transit solutions across cities.

💡 A Day in the Life

A typical day might involve designing a new data ingestion pipeline for real-time transit sensor data using Kinesis and Lambda, then reviewing data quality metrics in CloudWatch to ensure reliability. You could also optimize S3 storage strategies for cost efficiency while collaborating with AI teams to understand their data needs for urban safety models.

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Interview Prep

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🎯 Who Hayden AI Is Looking For

  • Has 6+ years building large-scale data systems with low latency requirements, specifically using AWS services like Kinesis/Kafka, Glue, EMR, and Redshift in production environments.
  • Demonstrates strong proficiency in Python, Scala, or Java for data processing, with experience optimizing pipelines for performance and cost in cloud environments.
  • Has hands-on experience implementing data quality frameworks, observability standards, and automated checks using tools like CloudWatch or Datadog for big data systems.
  • Understands data lifecycle management in S3, including partitioning strategies and retention policies that balance performance with cost efficiency for petabyte-scale datasets.

📝 Tips for Applying to Hayden AI

1

Highlight specific AWS data service experience with Kinesis/Kafka, Glue, EMR, and Redshift in your resume, quantifying scale (e.g., 'processed X TB daily using EMR').

2

Tailor your projects section to show experience with both streaming and batch data pipelines, emphasizing reliability and schema consistency across diverse sources.

3

Research Hayden AI's current transit projects in San Francisco or other cities and mention how your data platform experience could support those specific initiatives.

4

Include examples of implementing data quality checks and observability in previous roles, specifying tools used (CloudWatch, Datadog, or custom frameworks).

5

Demonstrate understanding of S3 optimization by describing partitioning strategies or lifecycle policies you've implemented to manage costs at scale.

✉️ What to Emphasize in Your Cover Letter

['Explain how your experience with AWS data services (Kinesis/Kafka, Glue, EMR, Redshift) directly applies to building scalable data platforms for real-time transit data.', 'Describe specific instances where you implemented data quality frameworks or observability standards that improved system reliability.', "Connect your background to Hayden AI's mission of safer, faster transit by discussing how reliable data pipelines enable better AI-driven urban solutions.", 'Mention experience optimizing data storage and lifecycle management in S3, showing awareness of cost-performance tradeoffs in production systems.']

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Hayden AI's specific transit projects in San Francisco or other cities, understanding the data sources and challenges they might face.
  • → The company's technology blog or case studies to see how they currently use AWS services for data processing.
  • → Urban transit challenges in San Francisco (congestion, safety initiatives) to contextualize how the data platform supports solutions.
  • → Recent news about Hayden AI's partnerships with municipal transit agencies to understand their growth and impact areas.

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Designing a data ingestion pipeline for real-time vehicle sensor data using Kinesis/Kafka and Lambda, ensuring low latency and reliability.
2 Implementing data quality checks and alerts for transit data streams using CloudWatch/Datadog, with examples of detecting anomalies.
3 Optimizing S3 storage for large-scale transit datasets, discussing partitioning strategies and lifecycle policies for cost management.
4 Migrating or evolving a batch processing pipeline to use AWS Glue and EMR, focusing on performance improvements and schema consistency.
5 Ensuring data platform reliability for AI models that inform transit decisions, discussing observability and disaster recovery approaches.
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⚠️ Common Mistakes to Avoid

  • Applying with generic data engineering experience without specific examples using AWS services mentioned (Kinesis/Kafka, Glue, EMR, Redshift).
  • Focusing only on batch processing without demonstrating experience with streaming data or low-latency systems as required.
  • Neglecting to discuss data quality, observability, or cost optimization in previous roles, which are key responsibilities listed.

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to Hayden AI!

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