Senior Data Engineer

hace 2 semanas

Colombia Agentic Dream A tiempo completo

At Agentic Dream, we're accelerating the transformation of global data landscapes. We're seeking highly experienced Senior Data Engineers to help deliver a robust and scalable data architecture across our global ERP systems.

If you're passionate about building end-to-end pipelines, enabling AI/BI solutions, and thriving in fast-paced, high-stakes environments, this is your challenge.

Learn more about us at:  

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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