Senior Data Engineer (Alteryx → Databricks Migration, Finance)
Koderia
Denmark
On-site
DKK 700,000 - 900,000
Full time
14 days+
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Job summary
Koderia is seeking a Senior Data Engineer to migrate finance cost allocation processes to Databricks, with SAP HANA as the source system. In this role, you will reverse-engineer Alteryx workflows, implement production-grade pipelines, and ensure successful handover to finance stakeholders. The ideal candidate has 5+ years of experience with Alteryx and Databricks, is capable of working independently, and has a strong understanding of financial data structures. Competitive remuneration offered.
Qualifications
5+ years relevant experience in Data Engineering.
Strong hands-on experience with Alteryx workflows.
Proficient in production-level Databricks engineering.
Responsibilities
Reverse-engineer existing Alteryx workflows and map data sources.
Translate transformation logic into PySpark/Spark SQL on Databricks.
Deploy and orchestrate Databricks pipelines with error handling.
Skills
Alteryx experience
Databricks engineering
PySpark
Spark SQL
SAP HANA experience
Finance domain literacy
Power BI
Unity Catalog
Tools
Delta Lake
SQL Server
Microsoft Excel
Job description
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.