Summary
As organizations accelerate their adoption of Agentic AI capabilities, the demand for robust data management and governance solutions is becoming increasingly critical. Atlas Data Science is seeking an L2/L3 Software Engineer to help build a central metadata hub that streamlines discovery, access, use, and sharing of diverse data types across an expanding ecosystem of suppliers and consumers. By orchestrating the full data lifecycle—from receipt to metadata capture and enrichment to discovery and dissemination—we aim to deliver a new-to-market data management and governance product that is foundational to enable agentic at scale.
Duties and Responsibilities
We are seeking a talented and motivated Software Engineer to join our dynamic and growing team. You will work alongside experienced engineers, leveraging a modern technology stack that includes TypeScript, Python, Java, Postgres, OpenSearch, Kubernetes, Airflow, Terraform, and GitLab. You will contribute to the development, testing, and productization of solution components integrating relational databases, microservices, cloud services, and containerized applications.
What You’ll Do
• Design, develop, and maintain data service metadata capture, transformation, and delivery pipelines.
• Integrate structured data from relational databases (Oracle, PostgreSQL, MySQL, etc.) into pipelines. • Optimize and troubleshoot pipelines for performance, reliability, and scalability.
• Contribute to backend service development using Java, Node.js, and Python.
• Implement infrastructure as code using Terraform to provision and manage platform resources. • Collaborate with DevOps to integrate pipelines into CI/CD workflows using GitLab.
• Write unit, integration, and system tests to ensure code quality and functionality.
• Support AI/ML initiatives by building and optimizing metadata pipelines for LLM training and data processing.
• Stay current with emerging technologies, development best practices, modern data lake/lakehouse frameworks, and evolving approaches in data brokerage services.
Required Competencies
• Proficiency developing production backend services using Python.
• Experience developing and integrating REST APIs and backend services.
• Understanding of Docker and deploying services in containerized environments.
• Experience with SQL, relational databases, and data modeling using platforms such as PostgreSQL, Oracle, or MySQL.
• Knowledge of authentication, authorization, secure API design, and secrets handling.
• Experience troubleshooting distributed services using logs and operational metrics.
• Strong communication, problem-solving, and collaborative development skills.
• Ability to work collaboratively in a team-oriented Agile environment.
• Experience diagnosing and improving backend performance, reliability, and scalability.
• Experience designing reliable asynchronous workflows, including retries, idempotency, timeouts, and failure handling.
• Experience with Airflow, Step Functions, Argo, or another orchestration platform.
• Experience with Git-based source control, code review, and CI/CD workflows; GitLab experience is preferred.
• Ability to decompose complex features into smaller deliverables and drive them from design through completion.
• Clear written and verbal communication skills.
Bonus Points
• Experience with AI assisted development.
• Experience with OpenSearch or another search engine. • Familiarity with policy engines such as OPA and authorization models such as RBAC or ABAC.
• Familiarity with OpenMetadata, DataHub, or another metadata-management platform.
• Experience or interest in modern data lake/lakehouse technologies (Apache Iceberg, Spark, etc.).
• Experience implementing semantic or hybrid search using embeddings, vector indexes, metadata filtering, and relevance ranking.
• Experience building LLM-powered workflows, including Retrieval-Augmented Generation, structured outputs, tool integration, evaluation, and production monitoring.
Other Requirements
• US Citizen and based in the US.
• 5+ years of experience.
• We are location-agnostic but candidates must be able to work CST or EST hours.
Interview Process
1. Intro to Atlas/ Candidate Q&A: 15 minutes with VP of Finance and Ops
2. Interview with VP of Engineering and/or Director of Product: 30 minutes
3. Technical Test: 30 minutes
4. Conversation with Hiring Manager: 60 minutes
5. Meet the CEO: 30 minutes
Why Atlas
Meaningful work. Our platform powers decisions that matter, from federal government to financial institutions to healthcare systems.
Benefits that make a difference. We pay competitively and back it up with equity, because we want you to have a real stake in what we build together. Beyond salary, here’s what you can expect to while working at Atlas:
- Healthcare coverage for you and your dependents, where Atlas pays 90% of the median plan cost
- 401 (k) matching at 100% up to 6% of your contribution
- Paid parental leave
- Unlimited PTO to take time off to recharge
- A remote work environment, so you can do your best work from wherever that happens to be
Skills Required
- US citizenship
- Based in the United States
- 5+ years of professional experience
- Ability to work CST or EST hours
- Production backend development experience using Python
- Experience developing and integrating REST APIs and backend services
- Understanding of Docker and containerized application deployment
- Experience with SQL, relational databases, and data modeling
- Knowledge of authentication, authorization, secure API design, and secrets handling
- Experience troubleshooting distributed services using logs and operational metrics
- Experience improving backend performance, reliability, and scalability
- Experience designing reliable asynchronous workflows with retries, idempotency, timeouts, and failure handling
- Experience with Airflow, Step Functions, Argo, or another orchestration platform
- Experience with Git-based source control, code review, and CI/CD workflows
- Strong communication, problem-solving, and collaborative development skills
- Ability to work in an Agile, team-oriented environment
- Ability to decompose complex features and deliver them from design through completion
- Experience with GitLab
- Experience with AI-assisted development
- Experience with OpenSearch or another search engine
- Familiarity with OPA, RBAC, or ABAC
- Familiarity with OpenMetadata, DataHub, or another metadata-management platform
- Experience with modern data lake or lakehouse technologies such as Apache Iceberg or Spark
- Experience implementing semantic or hybrid search using embeddings, vector indexes, metadata filtering, and relevance ranking
- Experience building LLM-powered workflows, including RAG, structured outputs, tool integration, evaluation, and production monitoring
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