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

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