Senior Data Engineer
airSlate
This is a senior data engineering role at a global SaaS company (airSlate) building no-code workflow automation and e-signature products. You'll be responsible for maintaining and expanding their data platform, building and optimizing data pipelines from internal databases and SaaS applications, and implementing DataOps practices. You'll work closely with analytics engineers and data analysts to support the company's growing analytical needs.
Brak jawnych widełek — wynagrodzenie do ustalenia podczas rekrutacji.
Brakuje: team size and composition, on-call rotation details.
This is a senior data engineering role at a global SaaS company (airSlate) building no-code workflow automation and e-signature products. You'll be responsible for maintaining and expanding their data platform, building and optimizing data pipelines from internal databases and SaaS applications, and implementing DataOps practices. You'll work closely with analytics engineers and data analysts to support the company's growing analytical needs.
- ✓Stock options and performance-based bonus system
- ✓Dedicated learning budget (courses, conferences, learning resources)
- ✓Quarterly company-wide Mental Health Days
- ✓Family-friendly culture (flexibility, pet-friendly, Junior Club)
- ✓Open communication culture with CEO Q&A sessions
- ✓Charitable initiatives and matching donations
- −None explicitly identified from the description.
- !The extensive list of required technologies may indicate a need for a broad skill set, potentially leading to unrealistic expectations.
- !Mention of using AI tools in the hiring process (some candidates may find this concerning).
- !Global team across multiple time zones could require asynchronous collaboration.
- ?Brak jawnych widełek — wynagrodzenie do ustalenia podczas rekrutacji
- •Maintaining and improving the existing data platform for timely, quality data delivery
- •Building and optimizing data pipelines from internal databases and SaaS applications using Apache Spark, Airflow, or similar tools
- •Writing maintainable code in Python/Scala/Java for data processing and orchestration
- •Creating and maintaining system documentation and best practices
- •Collaborating with Analytics Engineers and Data Analysts to improve their workflow efficiency
- •Implementing DataOps philosophy including CI/CD, monitoring, and data quality
- •Designing and extending the enterprise data model to support new requirements
- •Solving complex technical problems related to data platform scalability and performance
Oferta dla doświadczonych specjalistów (Senior).
A mid-level data engineer with at least 3 years of hands-on experience in data pipeline development using Python and Spark, comfortable with AWS and basic data modeling. Familiar with Airflow and CI/CD, and eager to grow into a senior role with ownership of the data platform.
Not for junior engineers or those without strong data engineering fundamentals. Also not for candidates seeking a purely analytical or research role — this is a hands-on engineering position focused on building and maintaining production data infrastructure.
- ?What is the current size and structure of the data engineering team?
- ?What are the main challenges with the existing data platform?
- ?Is the role more focused on building new pipelines or maintaining/optimizing existing ones?
- ?What is the on-call expectation for this role?
- ?Which specific cloud and data technologies are used in production, vs. aspirational?
- ?How mature is the DataOps culture currently at airSlate?
- ?What does the typical career progression look like for a Senior Data Engineer here?
- ?How involved will I be with other functions like product or business stakeholders?
- −Team size and composition
- −On-call rotation details
- −Detailed recruitment process (number of stages, technical assessment)
- −Specific tools currently used in production (beyond broad categories)
- −Performance review cycle and criteria for bonuses
Global, remote-first culture with flexible working, open communication across all levels, and emphasis on continuous learning and innovation. The team is distributed across hubs in the US, Poland, Romania, Ukraine, and Philippines.