Senior Business Intelligence Engineer - QuickSight, AWS, PySpark

GCS Recruitment Specialists; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

GCS Recruitment Specialists seeks a Senior BI Engineer to own and rebuild the manufacturing reporting layer, delivering scalable Amazon QuickSight dashboards. The role collaborates with operations, software engineering, and data engineering to validate metrics, redesign datasets, and automate reporting across AWS services such as Athena, Redshift, S3, Glue, and PySpark.

Strong SQL and Python/PySpark skills are essential.

Qualifications

• 5+ years of BI, analytics engineering, or data engineering experience.
• Ownership of the reporting layer end-to-end from source data to dashboards.
• Strong SQL with joins, window functions, and performance tuning.
• Hands-on Amazon QuickSight (SPICE, calculated fields, RLS) experience.
• Experience with AWS data platforms: Athena, Redshift, S3, Glue, PySpark.
• Python/PySpark for validation, profiling, and transformation.
• Experience with manufacturing or supply chain data is a plus.

Responsibilities

• Assess existing QuickSight dashboards, Athena/Redshift datasets, and workflows.
• Resolve data quality and reporting discrepancies.
• Validate KPIs with operations stakeholders.
• Rebuild and optimize the reporting layer from source to dashboards.
• Develop and automate WBR/MBR dashboards using QuickSight.
• Work with AWS data platforms including Athena, Redshift, S3, Glue, and PySpark.
• Implement reporting logic for calendars, shifts, utilization, throughput, etc.
• Create self-service datasets, templates, and documentation for users.
• Support future analytics and automation initiatives.

Skills

BI / Analytics

SQL

Amazon QuickSight

AWS (Athena, Redshift, S3, Glue)

Python / PySpark

End-to-end reporting

Data validation / profiling

Tools

Athena

Redshift

S3

Glue

Job description

Hiring Alert!

Job Title: Senior BI Engineer - (QuickSight, AWS, PySpark)

Job Description

We are looking for a Senior BI Engineer to own and rebuild the manufacturing reporting layer, ensuring accurate, trusted, and automated operational reporting. The ideal candidate will work closely with operations, software engineering, and data engineering teams to validate business metrics, redesign datasets, and deliver scalable QuickSight dashboards.

Key Responsibilities

• Assess existing QuickSight dashboards, Athena/Redshift datasets, and reporting workflows.
• Analyze and resolve data quality and reporting discrepancies.
• Validate KPIs and business metrics with operations stakeholders.
• Rebuild and optimize the reporting layer from source tables through dashboards.
• Develop and automate WBR/MBR dashboards using Amazon QuickSight.
• Work with AWS data platforms including Athena, Redshift, S3, Glue, and PySpark.
• Implement reporting logic for calendars, shifts, utilization, throughput, cycle times, on-time delivery, yield, and backlog metrics.
• Create self-service datasets, templates, and documentation for business users.
• Support future analytics, data, and automation initiatives.

Required Skills

• 5+ years of experience in BI, Analytics Engineering, or Data Engineering.
• Experience owning the reporting layer end-to-end, from source data through dashboards.
• Strong SQL expertise, including complex joins, window functions, and performance tuning.
• Hands-on experience with Amazon QuickSight (SPICE, calculated fields, row-level security, dashboards).
• Strong AWS experience with Athena, Redshift, S3, Glue, and PySpark.
• Python/PySpark experience for data validation, profiling, and transformation.
• Experience working with operational, manufacturing, supply chain, logistics, or production data.

Preferred Skills

• Manufacturing, MES, ERP, or shop-floor analytics experience.
• Experience supporting Amazon-style WBR/MBR reporting and KPI frameworks.
• Knowledge of operational metrics such as utilization, throughput, downtime, cycle time, yield, and on-time delivery.