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.