Senior Workforce Analytics & Power BI Engineer

Senior Workforce Analytics & Data Engineer

Location: Hybrid Setup in Paranaque ( Supporting U.S. Business Hours)

Job Type: Full-Time

Department: Business Operations & Analytics / Data Engineering

About the Role

Are you a data engineer or senior analyst who loves connecting complex datasets to real-world business strategy?

We are seeking an innovative, self-directed Workforce Analytics / Data Engineer to design, build, and scale our workforce data infrastructure and predictive models. In this role, you will bridge the gap between technical data architecture and strategic workforce decisions—connecting headcount, operational, and financial data to drive decisions around staffing, utilization, productivity, and labor cost efficiency.

You’ll collaborate directly with U.S.-based stakeholders to turn complex, ambiguous requests into robust data pipelines, repeatable analytical models, and executive-ready dashboards.

What You’ll Do

🛠️ Data Engineering & Architecture

• Build & Maintain Pipelines: Design, build, and optimize scalable ETL/ELT pipelines and data models connecting HR, operational, timekeeping, and financial datasets.
• SQL & Data Warehouse Management: Write advanced SQL queries, views, and data structures in cloud data warehouses (e.g., Snowflake) to support fast, reliable reporting.
• Data Quality & Governance: Validate source data, resolve data discrepancies, and establish automated checks to ensure key metrics (headcount, labor cost, utilization) are accurate and trusted.

📊 Workforce Analytics & Decision Modeling

• Repeatable Modeling: Build, document, and maintain scenario and forecasting models that connect revenue, labor cost, capacity, and workforce productivity.
• Dashboards & Visualization: Develop self-service Power BI or Tableau dashboards that allow leadership to track operational performance and workforce trends.
• Insight Delivery: Translate complex data into clear options, trade-offs, risks, and recommendations for executive leadership.

⚡ Automation & AI Enablement

• Workflow Optimization: Identify manual reporting bottlenecks and automate workflows using scripting (Python/SQL), automated pipelines, and modern BI features.
• AI Tooling: Apply AI tools appropriately for documentation, issue triage, process mapping, and insight summarization to scale team operations.

What You’ll Bring

Required:

• Experience: 5+ years in Data Engineering, Workforce Analytics, Business Intelligence, or Operational Data Modeling.
• Advanced SQL: Proven expertise writing, optimizing, and troubleshooting complex queries, CTEs, and window functions in a cloud data warehouse environment (Snowflake, BigQuery, Redshift, etc.).
• Data Modeling & BI: Deep experience in Power BI or Tableau (data modeling, DAX, dashboard optimization) paired with advanced Excel capabilities.
• Workforce Domain Knowledge: Strong understanding of core workforce metrics (e.g., headcount, attrition, capacity, billable utilization, productivity, labor cost, and shrinkage).
• Python Skills: Practical experience using Python for data transformation, automation, or predictive modeling.
• Stakeholder Management: Ability to work independently with remote U.S. stakeholders, translate vague requests into structured technical solutions, and communicate risks clearly.
• Education: Bachelor’s degree in Data Engineering, Statistics, Computer Science, Finance, Information Systems, or a related quantitative field.

Preferred:

• Master’s degree in Data Engineering, Business Analytics, or Data Science.
• Relevant certifications in cloud data platforms, Power BI, or Lean Six Sigma / Agile frameworks.
• Experience in professional services, consulting, BPO, or labor-driven business models.

Why Join Us?

• High-Impact Work: Your insights will directly shape executive decisions, staffing models, and financial planning.
• Remote Flexibility: Work from home with autonomy while collaborating closely with a supportive, global team.
• Growth & Upskilling: Continuous opportunities to work with modern data stack tools, AI automation, and advanced predictive analytics.