Data Engineer (Python)
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Key skills for this role
About the Role
Olik Global is seeking a Data Engineer with 5-6 years of experience for a 3-month contract in Dhahran/Khobar, KSA. The role involves building data pipelines for an MRO Inventory Optimization solution, including ingestion, cleansing, transformation, and optimization logic.
Key Skills for This Role
Responsibilities
- Build data ingestion pipelines from SAP material master and inventory feeds via API/OData into the warehouse
- Perform data cleansing and master data processing: standardizing material descriptions, deduplication, classification, handling incomplete records
- Build and orchestrate ETL pipelines using Airflow and 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
Requirements
- 5 6 years of experience in data engineering
- Production grade Python with modular design, packaging, logging, config management, unit testing (pytest)
- Strong proficiency in Pandas/NumPy for vectorized transformations, joins, groupby, handling large datasets
- Experience authoring Airflow DAGs, operators/sensors, scheduling, backfills, task dependencies, retries/SLAs
- Proficiency in BigQuery: writing performant SQL, partitioning/clustering, cost aware querying
- Advanced SQL skills: joins, window functions, CTEs, aggregation, query optimization
- Experience building and consuming REST APIs (FastAPI/Flask), request validation, pagination
- Immediate availability
Full Job Posting
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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