Description

Are you a talented and experienced Data Engineer with a passion for finance? Join our globally distributed company and play a pivotal role in building and maintaining robust data systems that power our financial reporting and business insights.

As a Financial Data Engineer, you will be instrumental in developing reliable data pipelines, analyses, and visualizations that empower data-driven decision-making across the organization. You will collaborate closely with analytics engineers, software developers, finance teams, and other stakeholders to transform complex financial data into accessible and actionable information.

Your mission will include: building and maintaining efficient ETL processes for financial data, developing and supporting internal reporting tools, designing key metrics to illuminate business performance, and creating high-quality analyses and dashboards to communicate insights broadly. You will work with large datasets, ensuring data quality and integrity, building and maintaining scalable reporting processes and self-service tools, and acting as a central point to help the organization effectively leverage its financial data for high-quality decision-making.

This role demands strong SQL proficiency, solid programming skills, expertise in data visualization tools, and a deep understanding of data warehousing principles. Experience working with finance/accounting teams and familiarity with SaaS business models will be highly valued. Above all, we are looking for someone who is self-directed, possesses a strong bias for action, communicates effectively through written channels, and thrives in our continuous learning, distributed work environment.

Responsibilities (What you will do)

• Build and Maintain Data Pipelines: Design, develop, and maintain robust and reliable extract, transform, load (ETL) pipelines to efficiently process financial data from various sources.
• Enhance Reporting and Analysis: Continuously improve existing reporting and analysis processes, implementing automation and simplifying self-service capabilities for internal stakeholders.
• Collaborate Cross-Functionally: Work closely with analytics engineers, software developers, finance and accounting teams, and other business stakeholders to understand their unique data needs and solve complex business problems.
• Deliver High-Quality Data Solutions: Build and deliver high-quality data solutions and infrastructure to effectively support the work of analysts, engineers, and data scientists.
• Design Business Metrics: Define and build key metrics and dimensions to effectively monitor product and overall business performance.
• Create Data Visualizations: Develop and maintain high-quality and reliable data visualizations and dashboards, effectively communicating key insights to a broad audience.
• Support Internal Tools: Maintain and extend our internal tooling used for reporting critical business metrics.
• Ensure Data Quality and Integrity: Proactively monitor and maintain the accuracy, quality, and integrity of financial data within our systems.

Qualifications and Experience

Must Have:

• SQL Proficiency: Demonstrated proficiency in using SQL for data extraction, wrangling, and synthesizing information from various data sources.
• Programming Skills: Proven experience in at least one general-purpose programming language (e.g., Python, Scala, Javascript, PHP) for data manipulation and automation.
• Data Visualization Expertise: Expertise in effectively telling stories with data and fluency in building impactful visualizations using at least one data visualization tool (e.g., Looker, Superset, Tableau).
• Experience with Large Datasets: Proven experience working with and processing large volumes of data.
• Data Warehousing Fundamentals: Strong understanding of data warehousing architecture, data modeling concepts (e.g., star schema, snowflake schema), and ETL/ELT principles.
• ETL/Data Pipeline Development: Hands-on experience with ETL processes and building and maintaining data pipelines.
• Problem-Solving and Critical Thinking: Strong analytical, problem-solving, and critical thinking abilities, with a meticulous attention to detail.

Nice to Have

• SaaS Business Model Understanding: Familiarity with the key metrics and operational aspects of a SaaS business model.
• Finance/Accounting Experience: Experience working directly with or within finance and accounting teams, with a focus on topline metrics and revenue/revenue recognition principles.
• Version Control: Experience working collaboratively within a version control system (e.g., Git, Phabricator).
• AI-Powered Efficiency: Experience leveraging AI tools to enhance personal data engineering efficiency and productivity.

Note: If you feel strongly that you have what it takes for this role but don’t check 100% of the boxes—that’s okay—we encourage you to apply anyway and highlight what you can bring to the table.