Data Engineer - Python/Spark

Description :

- Develop and optimize ETL/ELT pipelines for large and complex datasets

- Build and manage data lakes and data warehouses

- Ensure high performance, reliability, and scalability of data systems

Master Data Management (MDM) :

- Develop and maintain MDM frameworks for supplier, vendor, and material master data

- Ensure data quality, consistency, and standardization

- Implement data cleansing, validation, and enrichment processes

- Define and enforce data governance policies

Procurement Data & Integration :

- Collaborate with Procurement, Finance, and Supply Chain teams

- Manage supplier master, spend, contract, and catalog data

- Enable analytics such as spend analysis and vendor performance

- Integrate data from ERP systems and external sources

Data Governance & Quality :

- Establish and monitor data quality KPIs and SLAs

- Resolve data inconsistencies and duplication issues

- Support audits and compliance requirements

Collaboration :

- Build self-service data platforms

- Communicate complex data concepts to stakeholders

Mandatory Skills :

- Experience with ETL tools (Airflow, dbt)

- Hands-on with data warehouses (Snowflake, BigQuery, Redshift)

- Experience with Apache Spark, Kafka, Hadoop

- Familiarity with Delta Lake / Iceberg

- Strong understanding of data modeling and governance

- Experience with MDM frameworks

Preferred Skills :

- Understanding of procurement lifecycle

- Experience with AWS, Azure, or GCP

- Experience in global environments

Behavioral Skills :

- Strong analytical and problem-solving skills

- Excellent communication skills

- Ability to translate business needs into data solutions

- Collaborative mindset