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Elevating Enterprises Through The Power of Intelligent Digital Transformation #AchieveMore
Data Engineer
Location
Indonesia
Posted
61 days ago
Salary
0
Seniority
Mid Level
Job Description
Data Engineer
Kata.ai
• Design, build, and maintain scalable data pipelines, streaming infrastructure, and AI/ML data workflows that power data-driven products and enterprise AI solutions • Ensuring reliable, timely, and high-quality data is available across the organization • So that AI Engineers, Product teams, and enterprise clients can make accurate, insight-driven decisions and deliver intelligent customer experiences through Kata's AI and voice platforms
Job Requirements
- Bachelor's degree in Computer Science, Information Systems, Data Engineering, Statistics, or related field
- Relevant certifications (GCP Professional Data Engineer, Databricks, Airflow/Astronomer, etc.) are a plus
- 1–2 years of professional experience in data engineering, software engineering with data focus, or a related technical role
- Hands-on experience building or maintaining data pipelines in a production environment
- Practical exposure to at least one streaming or batch processing technology (Kafka, Spark, or Airflow)
- Familiarity with SQL and relational or columnar databases (BigQuery, PostgreSQL, Hive, or equivalent)
- Exposure to cloud data services on GCP or Azure
- Experience working in Agile/Scrum teams with sprint-based delivery
- 3–5 years of professional experience in data engineering, with at least 2 years building and operating production-grade pipelines
- Proven hands-on experience with Apache Kafka for real-time event streaming — including topic design, consumer group management, and at-least-once/exactly-once delivery patterns
- Demonstrated experience designing and maintaining batch workflows using Apache Airflow and large-scale data transformations with Apache Spark
- Experience working with BigQuery and/or Hive for large-scale analytics workloads, including query optimization and partitioning strategies
- Hands-on experience with Cassandra or similar NoSQL wide-column stores for high-write or time-series data use cases
- Experience supporting AI/ML data pipelines — feature engineering, training dataset preparation, or model inference data feeds
- Experience with data quality frameworks and implementing data observability practices in production environments
Benefits
- Flexible working hour for our employees
- Learning experience in Conversational AI Industry
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