About the Role

We are a high-growth technology company building scalable digital platforms and operational systems for global clients. We operate with a strong focus on product excellence, engineering quality, speed of execution, and operational clarity.

We are seeking a Data & Automation Engineer (People Systems) to build the data and automation backbone for our People/HR team. This is a foundational capability hire—you will build reliable pipelines from our internal systems, clean models behind every workforce metric, and design intelligent bots and automated workflows that handle routine operations and employee engagement.

Prior HR domain experience is not required; curiosity about how organizational operations work is.

Key Responsibilities

1. People Data Foundation

   • Build reliable data pipelines connecting core systems (HRIS/BambooHR, recruiting tools, performance platforms, and engagement surveys) into a unified cloud data warehouse.

   • Design clean, well-documented data models to ensure metrics like talent density, headcount, attrition, and overall organizational health are accurate, consistent, and automatically updated.

2. Automation & Intelligent Bots

   • Design and deploy automated workflows and interactive bots for routine operations and employee engagement (e.g., onboarding sequences, daily report flows, offer/document workflows, and Slack nudges).

   • Adopt an "automation-first" mindset: aim to cover repetitive tasks with an agent or bot first—even an automation that handles 20–50% of a manual process provides immediate leverage to the team.

3. Self-Service Analytics

   • Build intuitive dashboards and natural-language interface options so managers can access workforce insights independently without waiting for custom reports, while maintaining strict access controls.

4. Security, Governance & Reliability

   • Implement robust role-based access control (RBAC) and privacy guardrails for sensitive employee data.

   • Proactively monitor data pipelines and automated workflows, resolve operational failures quickly, and keep system documentation current.

Requirements

Must-Have

• 4+ years of experience in Analytics Engineering, Data Engineering, or BI Development, with strong proficiency in SQL and Python.

• Proven track record of building from scratch: Experience taking a data platform, pipeline, or automated system from concept to production. (Be prepared to share concrete examples and measurable outcomes).

• Modern Data Stack Proficiency: Hands-on experience with cloud data warehouses (BigQuery, Snowflake, PostgreSQL, etc.), modern data transformation and orchestration tools (dbt, Airflow, Airbyte), and BI/visualization platforms.

• Integration & Security Basics: Demonstrated experience working with REST APIs, workflow integration, and fundamental data security protocols (RBAC, PII handling).

• Autonomy & Ownership: Strong self-drive with an end-to-end ownership mindset—capable of driving projects forward independently without waiting for step-by-step direction.

• AI Competence: Active use of AI tools and intelligent agents in your day-to-day workflow, with the ability to demonstrate how they elevate your output.

• Reflective & Outcome-Driven: Ability to clearly articulate past technical trade-offs, failures, key learnings, and business impact using quantitative metrics.

Should-Have

• Experience with workflow automation platforms (e.g., n8n, Zapier, Power Automate) or building conversational bots on chat platforms (Slack, Microsoft Teams).

• Exposure to LLM-based, conversational, or natural-language analytics applications.

• Strong written and verbal communication skills in English, with the ability to explain complex technical concepts simply to non-technical stakeholders.

Nice-to-Have

• Prior exposure to HR, workforce, or CRM dataset structures.

• Google Cloud Platform (GCP) experience or relevant cloud certifications.

Note: This is a full-time, dedicated position. Concurrent freelance, part-time, or consulting arrangements are not permitted.