Were looking for a highly skilled and motivated Senior Data Engineer to join the Resolve (formerly DevOcean) team at our company. In this role, youll be responsible for designing, building, and optimizing the data infrastructure that powers our SaaS platform. Youll 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.
Youll 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.

We are looking for an experienced, opinionated, and highly technical Staff Data Engineer to define the long-term direction of our Data Platform.
This role is ideal for a senior data leader who combines deep hands-on expertise with strong architectural judgment, enjoys mentoring others, and takes full ownership of complex, high-scale data systems.
You will drive platform architecture, set engineering standards, and lead the design and delivery of scalable batch and streaming data solutions on AWS.
Key Responsibilities:
Technical Leadership & Architecture:
Own and evolve the overall data platform architecture-scalability, reliability, security, and maintainability.
Lead the long-term strategic direction of the platform, balancing performance, cost, and operational excellence.
Introduce and drive adoption of modern data paradigms: lakehouse (Iceberg), event-driven pipelines, schema-aware processing.
Data Lake & Architecture Ownership:
Design, model, and evolve the Data Lake architecture, including:
Storage layout and data organization
Data formats and table design (e.g., Iceberg)
Batch and streaming ingestion patterns
Schema governance and lifecycle policies
Define and promote best practices for data modeling, partitioning, and data quality.
Ensure the Data Lake supports analytics, ML workloads, and operational systems at scale.
Platform Engineering:
Design and build high-scale ETL/ELT pipelines leveraging Apache Spark (EMR/Glue) and AWS-native services.
Optimize production-grade pipelines using S3, Athena, Kinesis, Lambda, Step Functions, and EKS.
Lead the rollout of modern patterns such as lakehouse architectures and event-driven data pipelines.
Security & Governance:
Ensure alignment with AWS security best practices-IAM, encryption, auditing, and compliance frameworks.
Partner with security and governance teams to support regulated and sensitive data environments.
Mentorship & Collaboration:
Serve as a technical mentor to data engineers; elevate team capabilities.
Lead architecture reviews and cross-team design discussions.
Work closely with Data Science, ML Engineering, Backend, and Product teams to deliver end‑to‑end data solutions.