Data & Integration Engineer, Business Systems
F
FigmaBusiness systems
Remotely in the United StatesFull-TimeSenior
SalaryAnnual Base Salary Range: $153,000 — $296,000 USD
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Job Details
- Experience
- 5+ years of relevant engineering experience
- Required Skills
- PythonSQLSnowflakeCI/CDRESTful APIsData modeling
Requirements
- Have 5+ years of relevant engineering experience, including hands-on delivery of enterprise integrations and production data pipelines.
- Bring strong experience building and supporting API-led integrations.
- Understand API design, authentication, asynchronous processing, retries, and idempotency.
- Have hands-on proficiency in query languages and programming for data transformation, pipeline development, and automation.
- Have experience with Snowflake or a comparable cloud data warehouse, including data modeling, incremental processing, and query optimization.
- Have experience integrating enterprise business applications across Finance, GTM, or People systems.
- Have independently owned projects from requirements through production, including testing, monitoring, troubleshooting, and documentation.
- Collaborate with business stakeholders and engineering teams.
- Experience with dbt, Airflow, or comparable transformation and orchestration tools is a plus.
- Familiarity with change data capture, streaming pipelines, schema evolution, and historical backfills is a plus.
- Familiarity with quote-to-cash, billing, accounting, or financial reconciliation processes is a plus.
- Experience with Workday Studio, Salesforce Apex, or NetSuite SuiteScript is a plus.
- Knowledge of AWS services such as S3, Lambda, and SQS is a plus.
- A background implementing or maintaining SOX/ITGC controls, mentoring engineers, and establishing shared engineering standards is a plus.
Responsibilities
- Design, build, and operate integrations across CRM, ERP, and HR systems using MuleSoft, APIs, and event-driven architectures.
- Build and maintain batch and incremental data pipelines into Snowflake, using SQL and Python for transformations, validation, and automation.
- Develop data models and datasets for business operations, reconciliation, and reporting, and partner with Data Engineering on standards and ownership.
- Translate stakeholder requirements into technical designs, delivery plans, and measurable acceptance criteria.
- Support business-critical order-to-revenue workflows with reliable processing, clear ownership, and safe recovery from failures.
- Implement automated testing, monitoring, alerting, and data quality checks.
- Apply security and SOX/ITGC-aligned practices, including access controls, code reviews, CI/CD, and change management.
- Lead design reviews, mentor engineers, and establish reusable components, documentation, and engineering practices.
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