Senior Data Engineer - Real time analytics
Aircall
18 hours ago
Full-time
Remote
Worldwide
Aircall is a unicorn in the AI-powered customer communications space, trusted by more than 22,000 companies worldwide to help teams connect with customers across voice, SMS, WhatsApp, and AI in one workspace. The company’s momentum comes from a simple idea: make teams operate smarter, not harder. Its AI Voice Agent automates routine calls, AI Assist helps with post-call work, and AI Assist Pro provides real-time guidance so people can do their best work. Aircall is headquartered in Paris, with a North American hub in Seattle and teams across Madrid, London, Berlin, San Francisco, New York, Sydney, and Mexico City. The product is well received and the business is scaling quickly, backed by investors and driven by rapid AI innovation across multiple product lines. If you’re drawn to a fast-moving, product-led environment where impact is visible and decisions are fast, this could be the place for you.
Aircall operates with a clear set of values: they aim to be customer-obsessed, data-driven, and focused on meaningful outcomes. Ownership, continuous learning, and thoughtful speed are prized, and collaboration sits at the heart of how work gets done. The company is looking for a Senior Data Engineer to join the Engineering team, taking a central role in managing analytics and the event platform stack. As part of the Analytics & Data Platform group, you’ll help deliver real-time insights, monitoring, and robust analytical reports for more than 22,000 customers around the world.
A day in the life of a senior data engineer
In this role you’ll help shape the data pipelines that power Aircall’s real-time product analytics. You’ll design scalable, low-latency streaming solutions and oversee end-to-end delivery of key modules that provide near real-time data for product and customers. Translating business needs into practical data models, you’ll optimise architectures to handle large volumes of data, while identifying slow queries and refining them for better performance. You’ll write clean, scalable code in languages such as Scala, Python, and SQL, and you’ll participate in testing, deploying, and maintaining data-oriented systems in production. Expect to tackle challenging data problems using both structured and unstructured sources, and to contribute to performance optimization and live site monitoring alongside the wider engineering team. You’ll also mentor colleagues, sharing feedback and helping others grow their skills as part of a collaborative, security-minded group that delivers dependable, scalable solutions to Aircall clients.
What you’ll need to bring (must-haves)
- A technical bachelor’s degree in a field such as computer science or mathematics
- At least three years of hands-on experience with near real-time analytics
- At least five years working with a modern programming language like Scala, Python, Go, or TypeScript
- Demonstrated ability to design and operate complex data processing pipelines
- Experience modelling data, including star and dimensional schemas, using AWS Redshift
- Proven ability to optimise data queries for better performance
- A track record shipping and maintaining code in production
Nice-to-haves
- Familiarity with Kafka is a plus
Pay, benefits and practical details
This is a full-time remote position based in France. Aircall offers a competitive salary package and benefits that include health coverage, lunch/meal support, commuting options, and sports benefits. The company operates with a diverse, multi-national team and values an inclusive culture. The role sits within a global engineering organization, with a strong emphasis on data-driven outcomes and measurable impact.
Tips for applicants
- Put your near real-time analytics achievements front and center on your resume. Lead with a concise snapshot of your three-plus years in near real-time analytics and your five-plus years working with languages like Scala, Python, Go, or TypeScript, then back it up with concrete results and the data stack you used.
- Show concrete proof of the must-haves. Describe a project where you designed a complex data processing pipeline, how you modeled data in AWS Redshift, and a situation where you improved query performance. If you can quantify impact (latency improvements, throughput gains, cost reductions), include numbers.
- Prepare for interviews by telling a real-world story. Be ready to walk through a near real-time data problem you solved end-to-end: the business need, the data architecture you proposed, how you handled data quality and monitoring, and how you collaborated with teammates to deliver production-ready code.
- Ask a precise question about the data platform. For example, inquire about the current near real-time architecture, the primary metrics the team uses to gauge success, or how Aircall balances speed with data quality across live dashboards and reports.
How to apply
There are no additional application instructions or deadlines published here besides the general process. If you’re excited by real-time analytics, scalable data platforms, and partnering with product teams to deliver valuable insights, Aircall invites you to pursue this opportunity. For more about candidate privacy, you can review Aircall’s Candidate Privacy Notice here: https://aircall.io/candidate-privacy-notice/
Aircall operates with a clear set of values: they aim to be customer-obsessed, data-driven, and focused on meaningful outcomes. Ownership, continuous learning, and thoughtful speed are prized, and collaboration sits at the heart of how work gets done. The company is looking for a Senior Data Engineer to join the Engineering team, taking a central role in managing analytics and the event platform stack. As part of the Analytics & Data Platform group, you’ll help deliver real-time insights, monitoring, and robust analytical reports for more than 22,000 customers around the world.
A day in the life of a senior data engineer
In this role you’ll help shape the data pipelines that power Aircall’s real-time product analytics. You’ll design scalable, low-latency streaming solutions and oversee end-to-end delivery of key modules that provide near real-time data for product and customers. Translating business needs into practical data models, you’ll optimise architectures to handle large volumes of data, while identifying slow queries and refining them for better performance. You’ll write clean, scalable code in languages such as Scala, Python, and SQL, and you’ll participate in testing, deploying, and maintaining data-oriented systems in production. Expect to tackle challenging data problems using both structured and unstructured sources, and to contribute to performance optimization and live site monitoring alongside the wider engineering team. You’ll also mentor colleagues, sharing feedback and helping others grow their skills as part of a collaborative, security-minded group that delivers dependable, scalable solutions to Aircall clients.
What you’ll need to bring (must-haves)
- A technical bachelor’s degree in a field such as computer science or mathematics
- At least three years of hands-on experience with near real-time analytics
- At least five years working with a modern programming language like Scala, Python, Go, or TypeScript
- Demonstrated ability to design and operate complex data processing pipelines
- Experience modelling data, including star and dimensional schemas, using AWS Redshift
- Proven ability to optimise data queries for better performance
- A track record shipping and maintaining code in production
Nice-to-haves
- Familiarity with Kafka is a plus
Pay, benefits and practical details
This is a full-time remote position based in France. Aircall offers a competitive salary package and benefits that include health coverage, lunch/meal support, commuting options, and sports benefits. The company operates with a diverse, multi-national team and values an inclusive culture. The role sits within a global engineering organization, with a strong emphasis on data-driven outcomes and measurable impact.
Tips for applicants
- Put your near real-time analytics achievements front and center on your resume. Lead with a concise snapshot of your three-plus years in near real-time analytics and your five-plus years working with languages like Scala, Python, Go, or TypeScript, then back it up with concrete results and the data stack you used.
- Show concrete proof of the must-haves. Describe a project where you designed a complex data processing pipeline, how you modeled data in AWS Redshift, and a situation where you improved query performance. If you can quantify impact (latency improvements, throughput gains, cost reductions), include numbers.
- Prepare for interviews by telling a real-world story. Be ready to walk through a near real-time data problem you solved end-to-end: the business need, the data architecture you proposed, how you handled data quality and monitoring, and how you collaborated with teammates to deliver production-ready code.
- Ask a precise question about the data platform. For example, inquire about the current near real-time architecture, the primary metrics the team uses to gauge success, or how Aircall balances speed with data quality across live dashboards and reports.
How to apply
There are no additional application instructions or deadlines published here besides the general process. If you’re excited by real-time analytics, scalable data platforms, and partnering with product teams to deliver valuable insights, Aircall invites you to pursue this opportunity. For more about candidate privacy, you can review Aircall’s Candidate Privacy Notice here: https://aircall.io/candidate-privacy-notice/