Scopely is looking for an Analytics Engineer, Finance to join our Finance team in Barcelona, Spain , on a hybrid basis, working 3 days a week from our hub.
At Scopely, we care deeply about what we do and want to inspire play, every day - whether in our work environments alongside our talented colleagues, or through our deep connections with our communities of players. We are a global team of game lovers who are developing, publishing and innovating the mobile games industry, connecting millions of people around the world daily.
Show us the money! As the Finance team, we’re number crunchers with top-notch analytical and reporting skills. As a shared service, we get to work with all of Scopely's talented studios.
In this role, you will help to improve the reliability, accuracy, and maintainability of Finance data workflows by developing and supporting automated pipelines, data transformations, and reporting models. Working closely with stakeholders and the Lead Analytics Engineer in Finance, this role contributes to reducing manual processes, strengthening data quality, and ensuring dependable financial information for monthly close, revenue reporting, and accounting activities.
What You Will Do:
Partner with Finance stakeholders to understand business requirements, financial processes, and controls, translating them into practical technical solutions with guidance from the Lead Analytics Engineer.
Develop, maintain, and troubleshoot data pipelines, SQL transformations, and reporting models supporting monthly close, revenue reporting, and accounting workflows.
Investigate missing, delayed, inconsistent, or incorrect financial data, identify root causes, and implement reliable solutions.
Help modernize legacy SQL, scheduled workflows, and manual processes into maintainable, documented, and dependency-aware pipelines using dbt.
Build and improve automated data-quality checks, reconciliations, monitoring, and alerting to strengthen the reliability of Finance data workflows.
Apply Git, code review, testing, and deployment practices to improve the quality and maintainability of Finance data assets.
Support the automation of recurring spreadsheet-based processes and manual handoffs, while maintaining technical documentation, dependency maps, runbooks, and recovery procedures.
Collaborate with the Lead Analytics Engineer to apply engineering standards and contribute to governed, reusable models within the Looker semantic and reporting layer.
What We're Looking For:
Strong SQL skills and experience developing and maintaining production data transformations.
Experience working with a modern cloud data warehouse such as BigQuery, Snowflake, or Redshift.
Experience with data transformation frameworks such as dbt, Dataform, or equivalent technologies.
Knowledge of Git, version control, code reviews, and collaborative software development practices.
Familiarity with data-quality checks, automated testing, monitoring, or reconciliation processes.
Strong debugging and problem-solving skills, including the ability to investigate issues in inherited or imperfectly documented systems.
Experience working with Finance, Accounting, Revenue Accounting, month-end close, or audit-related data.
Ability to communicate technical concepts clearly to non-technical stakeholders, collaborate with engineering colleagues, and independently progress defined technical problems while seeking guidance when appropriate.
Openness to learning and responsibly using AI-supported tools to improve SQL development, documentation, debugging, testing, and workflow efficiency, while maintaining appropriate data security and validation practices.
Bonus Points:
Familiarity with financial controls, reconciliation, general-ledger concepts, or revenue recognition.
Experience in gaming, digital products, app-store revenue, or virtual economies.
Experience with data lineage, CI/CD, observability, or data governance practices.
Experience working with GCP, Airflow, Cloud Composer, or…