Data Engineer/Senior Data Engineer, Data and Science

Aircall; Santa Fe (NM); On-site; USD 100,000 - 150,000; Full time

Benefits offered by this job

Competitive salary package

Insurance coverage (medical, dental, 1

401k plan with company matching

Unlimited PTO

Wellness and commuter reimbursements

Parental leave

Job summary

Aircall, a unicorn AI-powered customer communications platform, is seeking a Data Engineer to build the data layer powering real-time dashboards and AI-ready analytics. You’ll own end-to-end data pipelines, collaborate with product, GTM, and analytics teams, and help scale our semantic layer for churn prediction and feature adoption.

We value hands-on engineers proficient in SQL and Python, with dbt and Airflow experience, cloud platforms (AWS/GCP/Azure), and a track record of delivering

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years of data engineering experience with data pipelines and infrastructure.
• Proficient in SQL and Python.
• 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 troubleshoot complex data issues and collaborate effectively across teams.
• Prior experience designing AI-ready data semantic layer is a major plus.
• Experience with data governance and data privacy is a plus.

Responsibilities

• Design, build and maintain core data infrastructure pieces to support various data use cases.
• Enhance the data stack, lineage monitoring and alerting to improve data quality.
• Implement best practices for data management, storage and security to ensure compliance.
• Own the core company data pipeline, translating business needs to reliable data pipelines.
• Participate in code reviews to ensure code quality and knowledge sharing.
• Lead efforts to evaluate and integrate new technologies and tools.
• Define and manage evolving data models and data schemas; manage SLAs for data sets.
• Collaborate with applied scientists, data scientists, analysts and stakeholders to drive efficiencies.
• Bridge raw data and AI-driven decision-making within the data organization.

Skills

SQL

Python

Data pipelines

Distributed computing

Communication

Cross-functional collaboration

Problem solving

Education

Bachelor's degree in Computer Science or Engineering

Tools

dbt

Airflow

AWS

GCP

Azure

Job description

Aircall is a unicorn, AI-powered customer communications platform used by 22,000+ companies worldwide to drive revenue, resolve issues faster, and scale customer-facing teams. We’re redefining customer communications by bringing voice, SMS, WhatsApp, and AI together into one seamless workspace.

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.

• 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.
• 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.

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.

Find our Candidate Privacy Notice here.