Data Engineer/Senior Data Engineer, Aircall
Data and Science
$130-220k
+ Equity
AI-powered communications platform
Open for applications
AI-powered communications platform
501-1000 employees
Open for applications
$130-220k
+ Equity
501-1000 employees
Company mission
To empower every professional to have rich conversations, so they can focus on closing deals and delighting customers.
Role
Who you are
- Bachelor's degree or higher in Computer Science, Engineering, or a related field
- 3+ years of experience in data engineering, with a strong focus on designing and building data pipelines and infrastructure
- Proficient in SQL and Python, with the ability to translate complexity into efficient code
- Experience with data workflow development and management tools (dbt, Airflow)
- Solid understanding of distributed computing principles and experience with cloud-based data platforms such as AWS, GCP, or Azure
- Strong analytical and problem-solving skills, with the ability to effectively troubleshoot complex data issues.Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment
- Prior experience designing AI-ready data semantic layer is a major plus, specifically for enabling low-latency, high-fidelity analytics at scale
- Experience with data tooling, data governance, business intelligence and data privacy is a plus
What the job involves
- The Data Engineering team at Aircall works on providing high-quality, reliable, and actionable data
- As an AI-first data team, we are currently in a pivotal transition to build a robust semantic layer that will power our AI-first data platform, enabling analytics at speed and democratizing intelligent insights across the company
- Some of the key problems we are currently solving include taking charge of data reliability, integrating new sources for raw data ingestion, and building sophisticated data models to power real-time dashboards and predictive analytics
- In this role, you will be instrumental in building new datasets for high-impact use cases such as churn prediction and feature adoption, while owning the end-to-end reliability and scalability of our data pipelines
- You will work closely with Product and GTM business teams, sitting at the heart of a larger data organization alongside Data Science, Analytics, and Applied Scientists to bridge the gap between raw data and AI-driven decision-making
- You'll design, build and maintain core data infrastructure pieces that allow Aircall to support our many data use cases
- Enhance the data stack, lineage monitoring and alerting to prevent incidents and improve data quality
- Implement best practices for data management, storage and security to ensure data integrity and compliance with regulations
- Own the core company data pipeline, responsible for converting business needs to efficient & reliable data pipelines
- Participate in code reviews to ensure code quality and share knowledge
- Lead efforts to evaluate and integrate new technologies and tools to enhance our data infrastructure
- Define and manage evolving data models and data schemas. Manage SLA for data sets that power our company metrics
- Collaborate with applied scientists, data scientists, analysts and other business stakeholders to drive efficiencies for their work, supporting complex data processing, storage and orchestration
Our take
Call centres have been a mainstay of sales teams for decades, with the human touch delivering an impression conversion rate of about 30% for inbound calls. However analogue call centres are physical infrastructure-heavy and unable to take advantage of the flexibility afforded by remote and hybrid ways of work. Aircall exists to change that, providing a cloud-based call centre infrastructure that allows sales teams to work from their home offices.
Aircall isn't the only company in this space, and it faces heavy competition from Cloudtalk, another cloud-based call centre solution. However Aircall stands out in the market by its use of open APIs and webhooks, making integration with existing productivity and helpdesk tools much easier, and its superior call quality. Aircall has developed a significant customer base with these strengths, with over 20,000 companies using its platform.
The company has raised significant funding in recent years, highlighting the confidence investors have in their offering. With a rapidly expanding presence in the US, European, UK and Australian markets and the recent addition of AI voice agents to handle business calls 24/7, Aircall is clearly set on innovating at scale.
Steph
Company Specialist at Welcome to the Jungle
Insights
0% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
Jun 2021
$120m
SERIES D
May 2020
$65m
SERIES C
Total funding: $225.6m
Company HQ
NoMad, New York, NY
Leadership
Scott Chancellor
(CEO)Prior to joining Aircall as CEO in 2023, Scott was CEO of Humu and Chief Product/Technology Officer at Apptio. He also spent 7 years at Amazon Web Services as a Director and General Manager of AWS Insights.
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