Senior Data Engineer

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:

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., Net Suite, Quick Books, 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.).

• 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, Dev Ops, Business Analysts).

• 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.

• 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.

• Implement bronze, silver, and gold layers for ingestion, cleaning, and curated datasets.
• Organize data structures for optimized use in Power BI and AI systems.

• Align global units of measure (lbs, kg, packaging, linear feet) across products and regions.
• Execute data deduplication, enrichment, and harmonization from disparate systems.

• 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.

• Provide ready-to-use, clean datasets to support BI dashboards and AI/ML use cases.

• Document pipeline architectures, data transformation logic, and integration points clearly.
• Ensure adherence to data governance policies and assist with metadata management.