Analytics Engineer (BigQuery/dbt)

Location: Jakarta, Indonesia; hybrid workplace

Company

hirify.global's Engineering department develops analytics and data engineering capabilities supporting analytics, reporting, and machine learning use cases.

What you will do

• Design, build, and maintain modular, tested dbt models on BigQuery across staging, intermediate, and marts layers.
• Own assigned data domains, including data quality, documentation, downstream projects, and stakeholder trust.
• Investigate data anomalies and work with data engineers and source-system owners to resolve root causes upstream.
• Partner with analysts, product managers, and business stakeholders to model datasets and define metrics.
• Contribute to governance frameworks, access control taxonomy tags, naming conventions, model ownership, and dbt CI/CD.
• Optimize BigQuery cost and performance, collaborate on CDC, streaming, and batch pipelines, and mentor junior analytics engineers.

Requirements

• 5+ years of experience as an Analytics Engineer, Data Engineer, or Data Analyst with a strong SQL and data-modeling focus.
• Strong SQL skills, including window functions, CTEs, and cloud-warehouse query optimization.
• Production experience with dbt sources, models, tests, macros, snapshots, and exposures.
• Hands-on experience with BigQuery or an equivalent cloud data warehouse such as Snowflake or Redshift.
• Understanding of dimensional modeling, including Kimball and modern data-modeling patterns.
• Experience with Git, CI/CD workflows, stakeholder communication, and self-directed data initiatives.

Nice to have

• Experience in fintech, investment, or financial services.
• Familiarity with Flink, Kafka, Spanner Change Streams, Debezium, or other streaming and CDC pipelines.
• Experience with data governance, column-level security, PII handling, and data catalogs.
• Python for data tooling and orchestration with Airflow, Dagster, or similar tools.
• Exposure to BI tools and product analytics platforms such as Looker, Metabase, Tableau, Amplitude, Mixpanel, or Segment.

Culture & Benefits

• Hybrid work arrangement in Jakarta, Indonesia.
• Strong emphasis on data correctness, root-cause resolution, and accountable data ownership.
• Opportunities to initiate improvements in testing frameworks, semantic layers, metric stores, internal tooling, and automation.
• Collaboration across analytics, data engineering, product, and business teams.