Solutions Data Engineer

What You'll Do

• Use our Data Studio and Data Platform to build and manage end-to-end data flows across connection, extraction, mapping, transformation, validation, and publishing.
• Analyze source system data to understand file structures, APIs, data relationships, and model requirements for new integrations and use cases.
• Connect FloQast to customer source systems including ERPs, file-based sources, APIs, and other upstream systems using supported connectivity patterns such as sFTP, APIs, and data sharing.
• Create mappings for new source systems and new FloQast data models, ensuring source data is accurately normalized for downstream application use.
• Map and transform source data into FloQast data models so it can be consumed consistently across FloQast applications.
• Build custom data models and transformation logic that extend FloQast's surface area to new systems and use cases, including non-ERP systems such as subledgers, banks, billing, payments, and other external platforms.
• Partner cross-functionally with customers, partners, Implementation, Customer Success, Product, and Engineering to turn business needs into working integrations and durable data solutions.
• Troubleshoot mapping, transformation, and publishing issues across customer implementations and internal platform workflows.
• Resolve data variances between source systems and published outputs to ensure accuracy, consistency, and trust in the data.
• Support successful customer launches by ensuring source data is connected, validated, and published accurately into FloQast applications.
• Scale integration patterns, mappings, and recipes so new sources can be onboarded more efficiently and consistently over time.
• Identify opportunities to improve Data Studio recipes, platform capabilities, and operating processes so integrations become faster, more scalable, and easier to support.

What You'll Bring

• 3+ years of experience in data integration, technical implementation, solutions consulting, analytics engineering, data migration, or a similar hands-on role.
• SQL, Python, and scripting skills, with hands-on experience working with data pipelines, APIs, file analysis, and file manipulation.
• Advanced proficiency in Microsoft Excel.
• Experience working with large CSV, TSV, and Excel-based source files.
• Experience working with structured and semi-structured data, transformation logic, schema mapping, and data validation.
• Experience cleansing, reshaping, and validating data for downstream consumption.
• Comfort working with incomplete, inconsistent, or messy source data.
• Strong communication skills and the ability to work effectively across customers, partners, Implementation, Customer Success, Product, and Engineering.
• Comfort operating in ambiguity and moving quickly without heavy process or close oversight.
• Strong debugging and troubleshooting ability across end-to-end data flows, including identifying root causes and driving issues to resolution.
• A practical ownership mindset with a bias toward getting working data into production safely and reliably.

Nice to have

• Experience working with financial data models and systems, such as hands-on experience with one or more major ERPs or accounting systems such as Oracle, SAP, Workday, or OneStream.
• Working knowledge of accounting and financial data, with the judgment to recognize when balances, relationships, or hierarchies do not make business sense.
• Experience working in a model-driven or metadata-driven data platform where source data is mapped, normalized, and published into reusable application-ready models.
• Experience creating custom transformation logic or custom data models to support downstream reporting, operational workflows, analytics, or application use cases.
• Experience troubleshooting customer-specific data issues in production environments, including source data defects, mapping gaps, schema mismatches, and transformation failures.