Senior Data Engineer (Alteryx → Databricks Migration, Finance)

SW House

Location –

Experience Senior, Medior

• Senior Data Engineer role focused on migrating two large-scale finance cost allocation processes from an Alteryx/SQL Server/Excel stack to Databricks, with SAP HANA as the primary source system.
• You will own the full technical arc from reverse engineering existing Alteryx workflows to implementing production‑grade, orchestrated Databricks pipelines and supporting handover and UAT.
• Engagement: Global Consumer Goods Company — Finance Data & Analytics; Location: Remote with occasional travel to client site (Denmark); Language: English (professional working level).

Key Responsibilities

• Reverse‑engineer the Alteryx estate:
  • Read and interpret ~15 Alteryx workflows (.yxmd) across two finance cost allocation processes.
  • Map and document all data sources (SAP HANA views, SQL Server tables, Excel master data files) and their roles in allocation logic.
  • Identify embedded formula logic, SQL pass‑throughs, manual input dependencies, and allocation key derivations.
  • Produce a structured technical inventory covering inputs, transformations, outputs, dependencies, and row volumes.
• Translate Alteryx transformation logic into PySpark / Spark SQL on Databricks.
• Connect directly to SAP HANA views as source and remove Alteryx as an intermediary layer.
• Re‑implement multi‑method cost allocation logic across Country / Channel / Theme / RRP dimensions natively in Databricks.
• Replace Excel master data inputs with managed tables in Unity Catalog where possible; flag where manual input processes require governance design.
• Structure output layers to match Silver/Gold conventions in the Databricks lakehouse platform.
• Deploy & orchestrate:
  • Deploy pipelines with scheduling, dependency management, and error handling.
  • Ensure Power BI reports can be repointed to Databricks‑served tables without functional regression.
  • Write runbooks and handover documentation for the internal engineering team.
  • Support UAT with finance SMEs, including reconciliation of output numbers against legacy Alteryx runs.

Requirements

• Seniority: Senior (5+ years relevant experience).
• Strong hands‑on Alteryx experience (able to read, trace, and independently document complex multi‑step workflows).
• Production‑level Databricks engineering using PySpark and Spark SQL (pipelines, not notebooks).
• SAP as a data source (SAP HANA views, BW extractors, or S/4 tables) and understanding of how financial data is structured in SAP.
• Finance domain literacy: cost allocation, P&L structures, overhead allocation methods (able to work with finance stakeholders).
• Ability to work independently from ambiguous/partially documented starting material.
• Unity Catalog, Delta Lake, DLT pipelines.
• Databricks orchestration (Workflows, job clusters, dependency graphs).
• Power BI (dataset repointing, dataflow or DirectQuery setup).
• Familiarity with SAP cost planning or profitability analysis processes (CO-PA, CPP).
• Experience replacing Excel‑based master data with governed catalog tables.
• Senior‑level engineering challenge focused on re‑architecture (not lift‑and‑shift).
• Direct access to finance SMEs and data engineers.
• Work within a modern Databricks / Unity Catalog lakehouse environment.
• Team support (you will not be working in isolation).
• Competitive day rate / project fee (T&M or fixed‑price per stream, depending on scoping outcome).
• Library/Framework: Spark SQL, pySpark
• Database: Delta Lake, SQL Server, SAP Hana
• Platform/Tool: Power BI, Delta Live Tables, SAP BW, Unity catalog, Alteryx, SAP S/4HANA, Databricks, Microsoft Excel, Databricks Workflows
• Programming language: SQL
• Project duration: Long‑term project
• Start date: May 6, 2026
• Contract type: Contract
• Language on the project: English