Senior Data Engineer | Remote LATAM Only

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.

Originally posted on Himalayas