5762 Data Engineer with AI skills

Summary

The Data Engineer role is primarily focused on building a modern analytics and Business Intelligence solution for the temp-staffing industry. The objective is to integrate operational data across multiple ERP systems to provide reliable insights, improve business decision-making, and enhance productivity through AI-driven methodologies.

Main Responsibilities

• End-to-End ETL & BI Development: Lead the development of scalable ETL/analytics pipelines from requirements through published datasets and dashboards for multi-tenant customer setups.

• Data needs & KPIs: Collaborate with stakeholders to clarify metrics, map them to ERP/operational data, and prioritize feasible and maintainable KPIs.

• ETL Pipeline Development: Build reliable pipelines that prepare analysis-ready datasets suitable for SQL-based reporting.

• BI Implementation: Design and implement BI dashboards that provide visual insights into KPIs for easy data interpretation.

• Scalability and Optimization: Ensure solutions can scale across multiple customers efficiently, optimizing performance as needed.

Key Requirements

• Strong ability to work independently in fast-paced environments.

• Proficient in advanced AI tooling, including MCP and harness engineering.

• Proven experience developing data pipelines with Python and Jupyter Notebooks.

• Hands-on use of Pandas, NumPy, and DuckDB (or equivalent) for processing.

• Familiar with cloud environments and SDKs for data extraction from Azure, AWS, and SQL databases.

• Expertise in SQL for data manipulation and creating normalized datasets.

• Experience with BI tools for dataset management and dashboard generation.

• Expertise in dashboard design for interactive data analysis.

• Experience with Apache Superset is a plus.

Nice to Have

• Hands-on experience with containerization technologies (e.g., Docker, Kubernetes).

• Knowledge of rights management in BI tools for data security.

• Familiarity with ETL parallelization and workflow orchestration.