RecargaPay

Specialist Analytics Engineer, Finance

RecargaPay

full-time

Posted on:

Origin:  • 🇧🇷 Brazil

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Job Level

Mid-LevelSenior

Tech Stack

FlashPySparkSQLTableau

About the role

  • Architect and implement scalable, high-performance analytical solutions by integrating SAP data with Databricks Lakehouse.
  • Lead the architecture and development of enterprise-grade Data Products, bridging SAP's business semantic layer and Databricks Lakehouse.
  • Design and implement robust data pipelines to extract and replicate data from SAP Datasphere into Databricks, using CDC and data synchronization best practices.
  • Transform and model complex SAP source data (Finance, Sales) within Databricks to build governed, performant, business-oriented data marts using PySpark and SQL.
  • Design and oversee development of dashboards and analytical layers in Tableau or QlikSense powered by curated Databricks data.
  • Act as data advisor for departments to define KPIs, conduct advanced analyses, and build data-driven decision frameworks.
  • Ensure standardization, governance, and version control of analytical solutions using dbt and Git, integrating with existing pipelines.
  • Champion analytical automation and data democratization, promoting self-service tools and internal training on SAP and Databricks stack.
  • Collaborate with Data Engineering, Product, and Technology teams to connect data to digital products, processes, and business strategies.
  • Mentor other analytics professionals and represent Analytics Engineering in governance, data quality, and architecture committees.

Requirements

  • Strong experience with SQL and PySpark for transforming, modeling, and processing large-scale, complex datasets, particularly from SAP systems.
  • Understanding of SAP data structures and core business processes (e.g., Finance (FI/CO)).
  • Proven ability to design and build analytical views and reusable data assets, aligned with business logic and performance standards.
  • Proficiency in visualization tools preferably Tableau or equivalent platforms (e.g., Qlik Sense, Power BI, Looker).
  • Hands-on experience with Databricks, including the development of business-oriented data marts and analytical models.
  • Familiarity with dbt, Git, and collaborative documentation tools (e.g., Confluence, Notion, Markdown-based wikis).
  • Ability to translate business requirements into governed, maintainable, and scalable analytical solutions.
  • Design cross-domain analytical solutions that are interoperable and scalable beyond individual products or squads.
  • (Nice to have) Proven hands-on experience with SAP Datasphere, including connecting to SAP source systems (e.g., S/4HANA), data modeling in the Business Builder, and creating consumption views for external access.