Head of Data Engineering & Analytics

About the Company

Manatal is an HRTech software service (B2B SaaS) headquartered in Bangkok, Thailand. Backed by Surge and Sequoia Capital, Manatal serves thousands of businesses in over 135 countries. Our mission is to offer AI-powered technologies to improve hiring for recruiters, hiring managers, and candidates.

About the Role

The Head of Data Engineering & Analytics will own the internal data platform end-to-end, reporting to the CTO. This is a hands-on individual contributor role to start, responsible for the data warehouse, ETL pipelines, BI tooling, and enabling teams across the organization to use data effectively. As the function matures, this person will grow the team. Onsite, full-time.

Responsibilities

• Own and manage the data warehouse (AWS Redshift): schema design, performance tuning, query optimization, workload management and cost control.
• Build, maintain and monitor ETL/ELT pipelines using Airbyte, Segment, Segment Reverse ETL and similar tools; ensure data quality, reliability and freshness; implement alerting and validation.
• Evaluate and introduce dbt (or equivalent) to add structure, version control and testing to data transformations.
• Integrate data sources across product, marketing, sales, finance and third-party services to create a unified source of truth.
• Own and manage Metabase as the primary BI platform: build core dashboards, data models and metrics definitions; drive adoption and reduce ad-hoc spreadsheet reporting.
• Build automated reports to replace manual recurring workflows and define/maintain core business metrics for consistency across teams.
• Coach and support Product, Marketing, Sales and Finance teams to enable self-service analytics through documentation, training and accessible data models.
• Connect marketing performance tools (e.g., Supermetrics) to the warehouse and consolidate paid acquisition, attribution and campaign data to measure campaign performance and ROI.
• Monitor and optimize data platform costs (Redshift compute and storage); recommend architectural changes (reserved instances, WLM, data lifecycle policies) and report trends to leadership.
• Own the internal data roadmap spanning Metabase, Retool integrations and marketing data infrastructure; prioritize initiatives with analysts and evaluate new tools as the function scales.

Qualifications

• 5+ years in data engineering, analytics engineering, or a combined data role at a technology company.
• Strong proficiency in SQL; experience writing complex queries, optimizing slow reports and designing data models.
• Hands-on experience managing a production data warehouse, preferably AWS Redshift, including schema design, query performance tuning, WLM configuration and cost optimization.
• Experience building and maintaining ETL/ELT pipelines; hands-on experience with Airbyte, Segment or similar ingestion tools is strongly preferred.
• Proficiency in Python for data pipeline development, scripting and automation.
• Experience with BI tools (Metabase, Looker, Tableau or equivalent) and owning a BI platform to build core dashboards and metrics.
• Demonstrated ability to coach and enable non-technical stakeholders to use data tools and build their own reports, and to improve data literacy across the organization.