Job Description

About us:

Populix is a consumer insights platform that helps businesses connect with its database of respondents and provides them with insights to better understand the preferences of Indonesian consumers. Populix has a pool of over 1,000,000 diverse, readily accessible, and highly qualified respondents across Indonesia. Its products range from intensive research studies to simple surveys and can be arranged on a project or subscription basis. Focusing on Indonesian consumers being super sticky to their phones, Populix facilitates a diverse range of data collection methods via its mobile app.

About the Role:

Populix is building the future of AI-powered market research, combining structured data, unstructured insights, and generative AI into a seamless research intelligence platform. As a Senior/Staff Data Engineer, you will be a technical leader responsible for designing, building, and maintaining scalable, reliable, and secure data pipelines and infrastructure. You will work closely with cross-functional teams including Product, Data Science, and Engineering to ensure high-quality, timely data powers business decisions across the organization.

This is a hands-on leadership role: you will write production-grade code, architect data solutions, mentor team members, and drive best practices in data engineering, governance, and security.

Key Responsibilities :

Design, build, and maintain production-grade ETL/ELT data pipelines using Python/Spark/Rust for data processing
Build and optimize data transformations and aggregations for analytical workloads, including complex SQL with CTEs, window functions, and analyzing query execution/query planner
Develop and manage workflow orchestration using Apache Airflow/Dagster/Prefect (or other orchestration tools)
Architect and maintain cloud-based data infrastructure on Google Cloud Platform (GCP), leveraging services such as BigQuery, Dataproc, Dataflow, Google Cloud Storage, Pub/Sub, Compute Engine, and Cloud Functions for Data and Machine Learning workload
Design data models and schemas that support OLAP analytics, reporting, and downstream machine learning use cases
Implement data quality checks, validation frameworks, monitoring, and alerting for pipeline health and data integrity
Ensure data systems comply with security standards, including ISO 27001, SOC Type 2, data privacy regulations like UU PDP, and internal information transfer policies
Create and maintain comprehensive documentation for data pipelines, data models, infrastructure, and operational procedures
Lead cross-functional collaboration with Data Analysts, Data Scientists, Product Managers, and Software Engineers to translate business requirements into scalable data solutions

Required Qualifications :

Bachleor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field
5+ years of experience in Data Engineering, Data Platform, or Software Engineering (data-focused roles)
Experience with analytics engineering tools such as dbt or Dataform is a plus
Familiarity with FastAPI or other Python web frameworks for data service APIs is a plus
Strong understanding of data governance, data security, and compliance frameworks (e.g., ISO 27001) is a plus