Companies in this catalog do not charge applicants. Never send money to apply.
We are looking for highly experienced Senior Data Engineers to help deliver a robust and scalable data architecture across global ERP systems.
This role is ideal for someone passionate about building end-to-end pipelines, enabling AI/BI solutions, and thriving in fast-paced, high-stakes environments.
You will contribute to the acceleration of global data transformation initiatives, ensuring modern, enterprise-ready data ecosystems.
Key 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 and 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 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
Collaborate closely with Data Architecture leadership 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.
Ensure adherence to data governance policies and support metadata management.
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 (NetSuite, QuickBooks, Salesforce, RF Smart, etc.)
Demonstrated experience with:
Master data frameworks, unit conversion, and ERP-to-warehouse mapping
Handling structured and unstructured data
Data modeling best practices (star schema, snowflake schema)
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 messaging/email tools.
Exposure to AI/ML pipelines, including data preparation for machine learning or anomaly detection.
