Why This Job is Featured on The SaaS Jobs
This Senior Data Engineer position stands out in the SaaS landscape because it sits at the intersection of security product data and platform reliability. The listing points to a mature, multi-customer SaaS environment where data is not a side system but a core product capability—supporting analytics, search, and reporting while handling large volumes of security findings across varied customer contexts.
From a SaaS career perspective, the role emphasizes the kinds of data-platform decisions that translate across modern subscription businesses: designing durable pipelines, shaping data models for multi-tenant use, and balancing performance with cost. Exposure to choices like when to keep workloads in an operational store versus moving them to analytical engines (e.g., ClickHouse/DuckDB) builds judgement that is valuable in any SaaS company scaling usage and query complexity. The collaboration described with backend, product, and analytics also reflects how data engineering influences roadmap outcomes in SaaS.
This role is best suited to an experienced engineer who prefers ownership of foundational systems, enjoys making architectural trade-offs explicit, and is comfortable partnering across functions to define “good enough” data contracts and observability. It will fit someone motivated by platform leverage rather than isolated reporting work.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Description
Accelerate Your Career in Cybersecurity
As a leader in Automated Security Validation, we help businesses around the world safely emulate real-world attacks to uncover their vulnerabilities. At Pentera, you will be at the forefront of cybersecurity innovation, working on advanced tools that challenge organizations' defenses and push the limits of security testing.
With over 400 team members and 1,100+ customers in more than 50 countries, Pentera is a growing company supported by top investors like Insight Partners, K1, and The Blackstone Group.
If you are looking to grow your skills, make a difference, and be part of an innovative team, Pentera is the place for you.
About the Role:
We’re looking for a highly skilled and motivated Senior Data Engineer to join the Resolve (formerly DevOcean) team at Pentera. In this role, you’ll be responsible for designing, building, and optimizing the data infrastructure that powers our SaaS platform. You’ll play a key role in shaping a cost-efficient and scalable data architecture while building robust data pipelines that serve analytics, search, and reporting needs across the organization.
You’ll work closely with our backend, product, and analytics teams to ensure our data layer remains fast, reliable, and future-proof. This is an opportunity to influence the evolution of our data strategy and help scale a cybersecurity platform that processes millions of findings across complex customer environments.
Roles and Responsibilities:
- Design, implement, and maintain data pipelines to support ingestion, transformation, and analytics workloads.
- Collaborate with engineers to optimize MongoDB data models and identify opportunities for offloading workloads to analytical stores (ClickHouse, DuckDB, etc.).
- Build scalable ETL/ELT workflows to consolidate and enrich data from multiple sources.
- Develop data services and APIs that enable efficient querying and aggregation across large multi-tenant datasets.
- Partner with backend and product teams to define data retention, indexing, and partitioning strategies to reduce cost and improve performance.
- Ensure data quality, consistency, and observability through validation, monitoring, and automated testing.
- Contribute to architectural discussions and help define the long-term data platform vision.
Requirements
- 8+ years of experience as a Data Engineer or Backend Engineer working in a SaaS or data-intensive environment.
- Strong proficiency in Python and experience with data processing frameworks (e.g., Pandas, PySpark, Airflow, or equivalent).
- Deep understanding of data modeling and query optimization in NoSQL and SQL databases (MongoDB, PostgreSQL, etc.).
- Hands-on experience building ETL/ELT pipelines and integrating multiple data sources.
- Familiarity with OTF technologies and analytical databases such as ClickHouse, DuckDB and their role in cost-efficient analytics.
- Experience working in cloud environments (AWS preferred) and using native data services (e.g., Lambda, S3, Glue, Athena).
- Strong understanding of data performance, storage optimization, and scalability best practices.
- Excellent problem-solving skills and a proactive approach to performance and cost optimization.
- Strong collaboration and communication abilities within cross-functional teams.
- Passion for continuous learning and exploring modern data architectures.
Nice to Have:
- Experience with streaming or CDC pipelines (e.g., Kafka, Debezium).
- Familiarity with cloud security best practices and data governance.
- Exposure to multi-tenant SaaS architectures and large-scale telemetry data.
We are an equal opportunity employer and we are committed to building a diverse and talented workforce. We do not discriminate on the basis of race, sex, religion, colour, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, medical condition, disability, or any other class or characteristic protected by applicable law. We welcome candidates from all backgrounds to join us!
