AI Data Engineering Lead - Scalable AI Pipelines

EY

Kebayoran Baru

On-site

IDR 350,000,000 - 700,000,000

Full time

14 days+
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Benefits offered by this job

Continuous Learning
Leadership Coaching
Diverse & Inclusive Culture
Flexible work

Job summary

EY is seeking an AI Data Engineer (Managerial) to help clients modernize data platforms and unlock AI-driven insights. You will design scalable, AI-driven data pipelines and work with Databricks, Snowflake, Spark, Kafka, and Airflow to deliver value across engagements.

This role offers exposure to innovative projects, collaboration with data scientists and stakeholders, and opportunities to shape architecture and proposals in consulting contexts at EY.

Qualifications

  • Bachelor’s degree in Computer Science, Engineering, or a related field.
  • Hands-on data engineering experience with modern data platforms.
  • Proficient in Python or Scala.
  • Experience in cloud environments, preferably Azure.

Responsibilities

  • Design and build scalable, AI-driven data pipelines for advanced analytics and ML use cases.
  • Work hands-on with Databricks, Snowflake, Spark, Kafka, and Airflow.
  • Develop and optimize data processing workflows for performance and reliability.
  • Collaborate with data scientists, analysts, and stakeholders to translate requirements into technical solutions.
  • Ensure data quality and governance across the data lifecycle.
  • Optional: contribute to solution architecture, proposals, and RFP responses.

Skills

Databricks
Snowflake
Airflow
Python/Scala
Azure
AI pipelines

Education

Bachelor's degree in Computer Science or related

Tools

Databricks
Snowflake
Microsoft Fabric
Spark
Kafka
Airflow

Job description

EY is seeking an AI Data Engineer (Managerial) to help clients modernize data platforms and unlock AI-driven insights. You will design scalable, AI-driven data pipelines and work with Databricks, Snowflake, Spark, Kafka, and Airflow to deliver value across engagements.

This role offers exposure to innovative projects, collaboration with data scientists and stakeholders, and opportunities to shape architecture and proposals in consulting contexts at EY.

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