Senior Business Systems Engineer I /Senior Backend Engineer -Serverless Architecture and ETL expertise

About the role

This role builds and operates backend integrations that connect human work with AI agents. You enable secure, reliable automation across SaaS platforms and data platforms. The work focuses on high-scale orchestration, resilient pipelines, and production operations.

Software engineers turn product ideas into working code. Engineers work in small teams, review each other's work, and ship in small batches. Most teams follow agile practices such as sprints and daily standups. Engineers also write tests, fix bugs, and improve performance. The field values clear communication as much as technical skill. Engineers spend part of every week on planning, code review, and debugging, not just writing new code. The ability to explain a technical decision in plain words separates strong engineers from the rest.

Key facts

Requirements

The posting states a minimum of 20 years of experience.

BS in Computer Science, related field, or equivalent industry experience as the baseline qualification for the role.

5+ years of experience in backend software development or automation using Node.js, Python, VS code or similar tools to build and maintain services.

Strong experience with AWS services, especially Lambda, S3, SQS/SNS, EventBridge, and DynamoDB for cloud-native implementation.

Expertise in database design, schema modeling, and query optimization, with a focus on DynamoDB & Snowflake to ensure performance and correctness.

Strong grasp of integration design patterns, secure API development (REST/SOAP), and system interoperability to connect applications safely.

Develop and maintain GitLab based CI/CD pipeline implementations for tests, linting, deployment, and other automation to streamline delivery.

Experience managing infrastructure as code using Terraform and CloudFormation to version and control cloud resources.

Demonstrated experience building and maintaining integrations with Salesforce, NetSuite, Workday, Coupa, Stripe, and Snowflake to enable core workflows.

Familiarity with data validation, schema evolution, and cross-system reconciliation is preferred to support data integrity across platforms.

Excellent collaboration and communication skills in a distributed, global team setting to work effectively across regions and time zones.

Confidence navigating production environments and owning critical issue resolution from end to end to maintain service reliability.

Experience delivering integrations and automation solutions across Finance, People, Sales, Legal, BI, and other functions to support enterprise needs.

Flexibility to adjust to changing priorities, new technologies, and evolving project requirements in a fast-moving environment.

Comfort operating in an Agile environment and participating in Sprint ceremonies such as Daily stand-up, Sprint planning, and Sprint Finalization to maintain rhythm.

Familiarity with prompt engineering and Generative AI for code generation is preferred to support efficient development practices.

Practical notes

Equal Opportunity Employer statement applies.

Typical interview steps

Hiring for engineering roles usually starts with a recruiter screen, followed by one or two technical rounds. Candidates often solve a coding problem, discuss past projects, and answer system design questions. Some loops include a take-home task. Final rounds typically cover team fit and give candidates a chance to ask questions. Interviewers look for how you break down an unfamiliar problem, not just whether you reach the answer. Practicing a few problems aloud and reviewing your own past projects are the best preparation.

Good to know

Serverless architectures remove server management so teams can focus on business logic at scale.

ETL pipelines move and transform data between sources, and CDC captures changes in databases in real time.

Event streaming platforms carry messages across services with low latency and high throughput.

Infrastructure as code keeps cloud environments versioned, repeatable, and auditable.

REST and SOAP APIs enable interoperability between different software systems.

CI/CD pipelines automate testing and deployment to reduce risk and speed delivery.

Agile methods coordinate work in timeboxed iterations with regular planning and review rituals.

Prompt engineering guides models to generate accurate code and content.