Data Analytics Engineer: Build Scalable Data Pipelines

Ctlyst; Jakarta Pusat; Hybrid; IDR 240,000,000 - 420,000,000; Full time

Job summary

AtCatalyst is seeking a Data Analytics Engineer to join our growing team. You will build reliable data pipelines, transform data, and develop dashboards to support business and product needs.

You will work with Product, Business, Finance, and Operations to translate business problems into data-driven solutions, ensure data accuracy and availability, and continuously improve our data platform and analytics processes for scalability.

Qualifications

• Minimum 2 years of experience in Data Analytics Engineering or related role.
• Strong SQL and data modeling skills.
• Experience using dbt and cloud data warehouses such as Snowflake or BigQuery.
• Experience building ETL/ELT pipelines and working with orchestration tools such as Prefect or Airbyte.
• Experience with BI tools such as Metabase, Looker, Tableau, or PowerBI.

Responsibilities

• Build and maintain reliable data pipelines, data models, and analytical datasets to support business and product needs.
• Transform and integrate data from multiple sources using SQL, dbt, Snowflake, and ETL/ELT tools.
• Develop and maintain dashboards, reports, and data solutions using Metabase.
• Work closely with Product, Business, Finance, and Operations teams to translate business problems into data-driven solutions.
• Ensure data accuracy, quality, consistency, and availability across critical business metrics.
• Continuously improve our data platform, automation, and analytics processes to make data more scalable and accessible.

Skills

SQL

Data modeling

dbt

Snowflake

BigQuery

ETL/ELT

Prefect

Airbyte

BI tools

Analytical thinking

Tools

Metabase

Looker

Tableau

PowerBI

Job description

AtCatalyst is seeking a Data Analytics Engineer to join our growing team. You will build reliable data pipelines, transform data, and develop dashboards to support business and product needs.

You will work with Product, Business, Finance, and Operations to translate business problems into data-driven solutions, ensure data accuracy and availability, and continuously improve our data platform and analytics processes for scalability.