Jobs at Atlas Systems

Test and validate Databricks data pipelines, data quality, transformations, and Power BI reports. Build automated tests using Python, Pytest, SQL, and PySpark; integrate tests into CI/CD; investigate defects and performance issues; track quality metrics; collaborate with engineering and business stakeholders; and mentor distributed QA testers.

Build, maintain, document, and modernize internal back-office web applications using C#, .NET, React, SQL, and Azure. Design cloud architectures, databases, APIs, caching, event-driven systems, and infrastructure as code. Lead legacy migrations, automated reconciliation testing, performance optimization, deployments, and staged releases. Collaborate with QA, business users, data engineers, offshore developers, and other teams while conducting code reviews and supporting agile delivery.

Owns manual and automated testing for internal web applications across API, UI, and database layers. Builds Playwright and API test suites, performs performance testing with JMeter, integrates tests into CI/CD pipelines, and ensures cross-browser quality. The role also establishes QA standards, reviews test code, tracks coverage and defects, collaborates with developers and business stakeholders, and mentors distributed QA testers in an agile environment.

Own requirements for a Databricks gold-layer data model supporting applications, data marts, reporting, and AI tools. Define metrics, mappings, business rules, and documentation; coordinate downstream stakeholders; manage questions and change requests; write issues and acceptance criteria; support QA, UAT, reconciliation, and migration testing; and provide status updates to leadership.

Own the Precisely Evolve and Automate Studio data-load layer for SAP S/4HANA. Build and maintain workflows, forms, scripts, and master-data loads; troubleshoot production failures across MDM, middleware, and SAP; support hypercare and operations; enforce change control, testing, versioning, and documentation; collaborate with SAP MM, PP, and SD teams; and transfer knowledge to reduce reliance on the original architect.

Develop and deliver Java applications using Spring Boot and related technologies in an Agile environment. Responsibilities include hands-on coding, business analysis, automated backend testing, manual UI testing, database development, production deployments, and client collaboration. The role also coordinates across engagements and represents Atlas in customer interactions.

Lead customer-facing AI solution architecture from presales through delivery. Identify AI use cases, design cloud-native solutions using Generative AI, LLMs, RAG, agents, and machine learning, develop PoCs, create proposals and architecture documents, support deal closures, and govern implementation. The role also drives AI-enabled full-stack engineering, DevSecOps, responsible AI, team mentoring, reusable accelerators, and executive stakeholder engagement.

Develop and maintain Java applications using Spring Boot and related backend technologies. Work with AWS, Kubernetes, Terraform, SQL databases, testing frameworks, React, TypeScript, and Datadog. Participate in coding, code reviews, business analysis, Agile ceremonies, production deployments, and collaboration with customer teams during U.S. working hours.

QA Specialist responsible for designing and executing QA strategies for Power BI reports and Microsoft Fabric data pipelines. Validate front-end report functionality, query SQL backends for data accuracy, automate testing (Playwright and pipeline tests), document test cases, track quality metrics, and collaborate with developers and data engineers to resolve data issues and ensure consistent reporting between legacy and Fabric environments.

Leads AI-assisted software delivery while combining business analysis, Scrum Master responsibilities, and hands-on technical leadership. Translates business needs into requirements, user stories, technical designs, and production solutions. Facilitates Agile ceremonies, manages dependencies, mentors developers, reviews code, and contributes to APIs, integrations, UI components, testing, CI/CD, and deployment automation. Ensures secure, responsible AI use, traceability, production readiness, stakeholder alignment, and measurable delivery improvements.

Develop and maintain secure, interactive data applications on Databricks using Python, Streamlit or Dash. Build user interfaces, connect to governed data through Databricks SQL and Unity Catalog, integrate REST APIs, and implement secure coding practices. Create tests, manage Git-based deployment workflows, troubleshoot production issues, document solutions, and collaborate with data, platform, security, and business teams. The role also involves SQL optimization, data governance, application performance, and responsible use of AI-assisted development tools.

Performs QA for ETL/ELT pipelines, data warehouses, migrations, semantic models, and Power BI reporting. Responsibilities include source-to-target reconciliation, data quality validation, transformation and load testing, SQL and Python-based automation, root-cause analysis, defect documentation, and validating Microsoft Fabric, Databricks, and Power BI environments. The role also develops reusable validation frameworks and integrates automated data-quality checks into CI/CD pipelines.

Maintain and enhance legacy Lotus Notes/HCL Domino applications across workflows, forms, security, routing, and shared components. Analyze undocumented applications, implement controlled production changes, troubleshoot access and workflow issues, support Domino 9-to-14 upgrade remediation, manage replication impacts, document application knowledge, and provide production support through ServiceNow. Collaborate with administrators and business stakeholders while supporting US Eastern hours and critical incidents.

Own the architecture, development, performance, and support of interactive WebGL product configurators integrated with Salesforce Commerce Cloud, SAP S/4HANA, PLM, PIM/MDM, middleware, OMS, and WMS systems. Translate customer configurations into accurate SKUs, bills of materials, prices, availability, and manufacturing orders. Lead front-end engineering, enterprise integrations, data contracts, asset pipelines, accessibility, personalization moderation, production support, and technical standards.

Lead architecture and implementation of scalable, distributed enterprise features across multi-cloud environments. Own full lifecycle from whiteboarding and design to coding, integrations, and post-launch stability. Build agent-driven workflows that connect autonomous AI agents to APIs and data pipelines. Execute as a hands-on individual contributor, leveraging AI tools to accelerate delivery while ensuring secure, observable, and extensible enterprise integrations.