Senior Backend/Data Infrastructure Engineer (Python/FastAPI/Kafka)

Why Join Tech9?

At Tech9, our vision is simple—help companies build exceptional software.

We partner with our customers to help them build and deliver world-class software through better UX/UI design, talent acquisition, and project management so that they can deliver quality code on time and on budget. You don’t have to just hear it from us—you can hear it from our customers: Instructure, Young Living, Imagine Learning, Mars Corp., and many others.

We’re growing fast, building an incredible team and services, and having plenty of fun as we do it in our US, LATAM, and India offices.

If a fast-paced environment with a need to build and scale sounds like fun, we highly encourage you to reach out. We’d love to partner with you on our journey to change the world of software development!

Project Overview 
Tech9 is working with a client who provides a cutting-edge risk analytics platform utilizing AI and machine learning to identify narratives and adversarial threats. The company handles large-scale, sensitive data, where efficiency in data management directly impacts both product performance and operational costs.
Tech9 is helping the client with a strategic migration of its data outputs from Snowflake to Postgres as part of a cost optimization initiative. The goal is to reduce backend compute charges tied to frontend data pulls. This migration is not just a technical upgrade, but a cost-saving strategy designed to improve the efficiency of data handling while maintaining data integrity and performance.

In addition to the migration work, this role will involve building and enhancing features using FastAPI alongside Python for fast, scalable API development and efficient system integration. The team is focused on optimizing backend performance while ensuring the product can handle large-scale data processing and real-time risk detection effectively.

Key Responsibilities

• Data Migration: Lead the migration of aggregated and cleaned data from Snowflake to Postgres while ensuring minimal impact on performance and data integrity.

• Cost Optimization: Implement strategies to reduce compute costs associated with frontend data pulls and optimize database performance.

• System Integration: Leverage Python and FastAPI to build and maintain efficient back-end systems, APIs, and data pipelines.

• Performance Monitoring: Ensure efficient data pipeline performance through detailed monitoring, validation, and post-migration optimization.

• Collaboration: Work closely with a lean team of technical experts and business stakeholders, contributing to a high-performance culture through efficient and clear communication.

Job Requirements

1. Technical Expertise

   • Python & FastAPI: Extensive experience (6+ years) with Python, particularly FastAPI, for building and maintaining high-performance backend systems, APIs, and data pipelines.

   • Snowflake: experience in Snowflake, with a focus on warehousing, performance tuning, cost management, and scaling.

   • Postgres: Deep knowledge of Postgres, including data modeling, indexing, query optimization, and handling analytics or API-facing workloads.

   • Airflow: Experience with Airflow for orchestrating, managing dependencies, job scheduling, and setting up alerting mechanisms.

2. Migration Experience

   • Strong experience owning or supporting migrations between cloud data warehouses and relational databases (especially Snowflake to Postgres).

   • Strong understanding of schema design trade-offs, cost implications, data quality maintenance, and transformation strategies.

   • Ability to validate and monitor pipeline reliability post-migration using appropriate tools and techniques.

3. Cost & Performance Awareness

   • In-depth understanding of Snowflake’s compute pricing model and how to minimize unnecessary charges, particularly related to frontend data pulls.

   • Experience in optimizing data workflows to reduce overuse, duplication, and excessive queries.

4. Understanding Product Impact

   • Awareness of how the data infrastructure supports critical AI/ML outputs, analyst workflows, and real-time risk detection in the platform.

   • Focus on delivering clean, fast, and reliable data to ensure operational efficiency and accuracy.

5. Collaboration & Dedication

• Ability to work independently and ramp up quickly in a lean, fast-paced team.
• Strong communication skills and the ability to collaborate with both technical peers and business stakeholders.

Interview Process Overview:

Below you'll find an outline of the interview plan for this Sr. Software Engineer positions. Please note that this is what we expect the process to look like; we may ask you for supplemental information or require an additional step before making a final decision.

1. Screening interview on-demand HireVue (15-30 min - Online Assessment)
2. 10-minute Q&A with Recruiter (can happen simultaneously with the assessment
3. 1 round interview with senior member of Engineering team (1 hour - Zoom)
4. 2nd round interview with a Principal member of Engineering team (1 hour - Zoom)
5. Client round meet and greet (30 minutes - Zoom)