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Data Engineer/Senior Data Engineer, Data and Science
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AstreyaUnited StatesPOSITION OVERVIEWThe Data Engineer is responsible for the integration build, data pipeline construction and operations, connector implementation, ETL development, and Astreya proprietary data pipeline
Über
Our momentum comes from a simple idea: help teams work smarter, not harder. Aircall's AI Voice Agent automates routine calls, AI Assist streamlines post-call work, and AI Assist Pro delivers real-time guidance so people can do their best work. The result is higher revenue, faster resolutions, and teams that scale with confidence.
Aircall is headquartered in Paris, our European HQ, with a strong North American presence anchored in Seattle, our North American HQ, and teams across Madrid, London, Berlin, San Francisco, New York City, Sydney, and Mexico City. We've built a product customers love and a business that's scaling quickly, backed by world-class investors and driven by rapid AI innovation across multiple product lines.
At Aircall, you'll join a company in motion. We're ambitious, product-driven, and execution-focused, with visible impact, fast decisions, and real growth.
How we work at Aircall:
We're customer-obsessed, data-driven, and focused on delivering meaningful outcomes. We value ownership, continuous learning, and thoughtful speed. If you thrive in a collaborative, fast-moving environment where trust and impact matter, you'll feel at home here.
About the role
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.
Responsibilities
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 A little more about you:
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.
$130,000 - $200,000 a year
This is not including equity and other benefits. The actual salary offered will carefully consider a wide range of factors, including your skills, qualifications, and experience.
Why join us?
Key moment to join Aircall in terms of growth and opportunities
Our people matter, work-life balance is important at Aircall
Fast-learning environment, entrepreneurial and strong team spirit
45+ Nationalities: cosmopolite & multi-cultural mindset
Competitive salary package & benefits
Medical, dental, and vision insurance is 100% covered
401k plan with company matching!
Unlimited PTO - take the time you need to come to work feeling great!
Wellness, commuter, and childcare reimbursements
Generous parental leave policy
DE&I Statement:
At Aircall, we believe diversity, equity and inclusion - irrespective of origins, identity, background and orientations - are core to our journey.
We pride ourselves on promoting active inclusion within our business to foster a strong sense of belonging for all. We're working to create a place filled with diverse people who can enrich and learn from one another. We're committed to ensuring that everyone not only has a seat at the table but is valued and respected at it by providing equal opportunities to develop and thrive.
We will constantly challenge ourselves to make sure that we live up to our ambitions around diversity, equity and inclusion, and keep this conversation open. Above all else, we understand and acknowledge that we have work to do and much to learn.
Want to know more about candidate privacy? Find our Candidate Privacy Notice here.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Sprachkenntnisse
- English
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