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.