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https://www.agenticdream.com/solutions Requirements
Technical Requirements: 7+ years of experience in enterprise-scale data engineering. Strong proficiency in: SQL (Advanced) and Python for Data Processing. Spark or Databricks for distributed data workflows. Cloud platforms such as Azure Data Lake/Blob, Synapse, or equivalents. ETL orchestration tools like Azure Data Factory (ADF), Airflow, or dbt. API integrations and data ingestion from ERP systems (e.g., NetSuite, QuickBooks, Salesforce, RF Smart, etc.). Demonstrated experience with: Master data frameworks, unit conversion, and ERP-to-warehouse mapping. Handling both structured and unstructured data. Data modeling best practices (star schema, snowflake schema, etc.). Soft Skills & Work Commitment
Fluent English (C1 level) – required for daily client calls and clear technical documentation. Strong interpersonal and collaboration skills to work with cross-functional teams (BI, QA, DevOps, Business Analysts). Nice to Have
Experience standardizing data across global manufacturing or supply chain environments. Familiarity with Power BI datasets, alert triggers, and integration with Microsoft Teams/email. Exposure to AI/ML pipelines, including data preparation for machine learning models or anomaly detection systems. Responsibilities
Data Integration & Pipeline Development
Design, build, and maintain scalable ETL/ELT pipelines from diverse ERP sources into centralized Data Lakes and Warehouses. Develop connectors for structured/semi-structured data using Python, SQL, APIs, or middleware solutions. Data Lake & Warehouse Engineering
Implement bronze, silver, and gold layers for ingestion, cleaning, and curated datasets. Organize data structures for optimized use in Power BI and AI systems. Data Standardization & Cleansing
Align global units of measure (lbs, kg, packaging, linear feet) across products and regions. Execute data deduplication, enrichment, and harmonization from disparate systems. Architectural Collaboration
Work closely with the Data Architect Lead on schema definitions, partitioning strategies, and infrastructure design. Set up and maintain sandbox/staging environments for safe testing. Power BI & AI Enablement
Provide ready-to-use, clean datasets to support BI dashboards and AI/ML use cases. Documentation & Governance
Document pipeline architectures, data transformation logic, and integration points clearly. Ensure adherence to data governance policies and assist with metadata management.
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Compétences linguistiques
- English
Avis aux utilisateurs
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