Data Engineer (Python)
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About the Role
**Experience:** 5-6 years | **Location:** Dhahran/Khobar, KSA — onsite only | **Duration:** 3 months (extension possible) | **Availability:** Immediate **Role Overview** Build the data backbone of the MRO Inventory Optimization solution — ingestion, cleansing, transformation, and the optimization logic that turns raw SAP material master and inventory data into actionable outputs. You'll own pipelines from source through to the analytics and application layers.
Key Skills for This Role
Full Job Posting
Experience
5-6 years |
Location
Dhahran/Khobar, KSA — onsite only |
Duration
3 months (extension possible) |
Role Overview
- Build the data backbone of the MRO Inventory Optimization solution — ingestion, cleansing, transformation, and the optimization logic that turns raw SAP material master and inventory data into actionable outputs.
- You'll own pipelines from source through to the analytics and application layers.
- Must-Have — technical depth expected
- Python: Production-grade code, modular design, packaging, logging, config management, unit testing (pytest); strong grasp of data structures and performance
- Pandas / NumPy: Vectorized transformations, joins/merges, groupby/aggregation, handling large datasets, deduplication, type coercion, working with messy real-world MRO/master data
- Airflow: Authoring DAGs, operators/sensors, scheduling and backfills, task dependencies, retries/SLAs, idempotent pipeline design, parameterization
- BigQuery: Writing performant SQL, partitioning/clustering, cost-aware querying, loading/exporting data, working with nested/repeated fields
- SQL: Advanced joins, window functions, CTEs, aggregation, query optimization across relational and warehouse engines
- API development: Building and consuming REST APIs (FastAPI/Flask), request validation, pagination, integration with upstream systems (e.g., SAP-sourced data via CPI/OData)
Good-To-Have
- PySpark (distributed transforms), ML basics (forecasting/classification relevant to inventory optimization — EOQ, demand forecasting, slow-moving/obsolete stock detection), data quality frameworks (Great Expectations or similar), Docker, CI/CD.
- Scope of Work
- Data ingestion from SAP material master and inventory feeds (via API/OData) and other sources into the warehouse
- Data cleansing and master data processing — standardizing material descriptions, deduplication, classification, handling incomplete records
- Build and orchestrate ETL pipelines (Airflow → BigQuery), ensuring reliability, idempotency, and data lineage
- Implement inventory optimization logic (reorder points, safety stock, EOQ, criticality/ABC analysis, obsolescence flags)
- Develop backend services / APIs exposing processed data to the UI and BI layers
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