Bixal

Data Engineer

• Lead the design and implementation of complex data ingestion pipelines using PySpark, Databricks Intelligence Platform, and AWS services (S3, IAM roles and policies), including Kafka/streaming architectures, schema evolution, and Delta Share, ensuring alignment with enterprise architecture standards.
• Serve as a subject matter expert (SME) for data engineering, providing technical guidance and mentorship to engineers across the team and representing data engineering in cross-functional discussions.
• Take ownership of platform reliability and performance, proactively identifying optimization opportunities across data ingestion, transformation, and storage layers.
• Troubleshoot complex pipeline failures across multi-system dependencies.
• Lead cross-functional technical initiatives, collaborating with data scientists, analysts, DevOps engineers, client teams (upstream data providers and downstream consumers), and stakeholders to deliver integrated solutions that meet program objectives.
• Contribute to the data platform technical vision and architecture, making strategic decisions on tooling, frameworks, and design patterns that shape the program's long-term data engineering direction.
• Define and enforce engineering standards, including code quality, testing practices, CI/CD processes, and infrastructure as code patterns using Terraform.
• Evaluation of new technologies and approaches, presenting proof of concepts and technical roadmaps to leadership.
• Author and maintain architectural documentation, technical decision records, and platform runbooks that enable team autonomy and operational excellence.
• Other relevant duties as assigned and qualified/trained to perform.

Full-stack Engineer

• Lead the design, development, and deployment of the Generic Data API Platform — a reusable Terraform module and Lambda-based pipeline that enables rapid onboarding of new data source APIs across different programs without custom infrastructure builds per dataset.
• Complete and deliver remaining platform phases: implement generalized data validation logic; work with data source teams to implement and configure endpoint querying logic; implement API capability discovery endpoints; conduct end-to-end integration testing across platform components; lead security review and performance validation; and drive the initial dataset API to production go-live.
• Implement OAuth 2.0 machine-to-machine authentication via AWS Cognito, ensuring that external consumers can authenticate against the platform with appropriate scope enforcement and usage-tier access controls.
• Champion the API platform internally — serve as the primary point of contact for partner data teams seeking to onboard new datasets, define the onboarding contract, and guide teams through the configuration and deployment process
• Develop and maintain operational runbooks, FHIR API documentation, and data team onboarding guides that enable partner teams to self-serve troubleshooting and data refreshes without requiring infrastructure team involvement.
• Own platform SLOs: API availability > 99.9%, error rate < 0.1%, and p95 response time < 500 ms.
• Define CloudWatch alarm thresholds appropriate to catch degradation before SLOs are breached, not after.
• Lead the API migration to the generic platform (Phase 2), validating that the module generalizes and establishes shared operational patterns across multiple concurrent datasets.
• Coordinate across teams to advance platform delivery: work with partner data teams on data delivery contracts, timelines, and search parameter definitions; engage CloudOps on security reviews and network security configuration changes; align with solutions architects on platform generalization and multi-dataset scale decisions; and involve data strategists when new data sharing agreements are required for a partner onboarding.
• Enforce defense-in-depth security controls across all platform deployments: network-layer threat protection, encryption at rest and in transit, identity and access management, API key lifecycle management, and long-term audit log retention.
• Monitor and optimize cloud infrastructure costs across platform deployments, leveraging serverless billing models, data lifecycle policies, and right-sized compute configurations to keep per-dataset costs sub-linear as the platform scales to 10 or more concurrent datasets.
• Contribute to and maintain cloud infrastructure Terraform across infrastructure and application repositories, including importing manually managed cloud resources, refactoring existing modules, and applying community best practices.

Senior Software Engineer

Technical Product Manager

• Define and drive the technical product strategy for the platform, aligning system architecture, platform capabilities, and integrations to measurable business and operational outcomes.
• Translate complex technical constraints into clear, actionable requirements and roadmaps that engineering teams can execute against.
• Lead large-scale modernization work, including platform evolution, service decomposition, and migrations, while protecting system stability and keeping delivery moving.
• Prioritize and sequence work across multiple teams, balancing technical dependencies, risk, performance, and long-term maintainability.
• Partner hands-on with engineering, platform, data, and design teams to resolve ambiguity and make sound tradeoffs.
• Communicate technical decisions, risks, and tradeoffs clearly to senior government stakeholders.
• Other relevant duties as qualified/trained to perform.

Data Engineer

Senior Software Engineer

Staff Technical Product Manager