Senior Data Engineer (Smart TV OS)

JonDavidson Pte Ltd; Singapore; On-site; SGD 110,000 - 180,000; Full time

Job summary

JonDavidson Pte Ltd in Singapore seeks a Senior Data Engineer to lead the end-to-end design, construction, and iteration of real-time data ingestion systems and streaming data warehouse architecture.

You will work at the intersection of high-scale streaming, cloud analytics, and business-critical dashboards to support real-time insights and monitoring, partnering with product managers and analysts to build production pipelines.

Qualifications

• Bachelor’s degree or higher in CS, software engineering, data science, or related field.
• 3+ years of professional big data engineering in high-scale environments with real-time pipelines.
• Strong Python/Scala/Java and Linux scripting skills.

Responsibilities

• Own real-time ingestion pipelines for logs, user data, and DB logs with stability and low latency.
• Design multi-layer real-time data models and streaming ETL workflows.
• Tune and operate Kafka, Spark, and Flink components for sub-second latency.
• Collaborate with data product managers, analysts, and stakeholders to translate requirements into production pipelines.

Skills

Python

Scala

Java

Shell scripting

Linux

Education

Bachelor's degree or higher in CS/Software Eng/Data Science

Tools

Apache Kafka

Apache Spark

Apache Flink

CDC

BigQuery

dbt

Google Cloud Platform

Job description

We are seeking an experienced Senior Data Engineer to join our client fast-growing team in Singapore. In this role, you will lead the end-to-end design, construction, and iteration of our real-time business data ingestion systems and streaming data warehouse architecture.

You will work at the intersection of high-scale real-time data streaming, cloud analytics platforms, and business-critical analytics engines to support real-time dashboards, user profiling platforms, and business monitoring systems.

Key Responsibilities

• Ingestion Pipeline Ownership: Own the lifecycle development of real-time collection, cleaning, and warehousing of business logs, user behavior data, and database operational logs to guarantee pipeline stability, completeness, and low latency.
• Real-Time Data Warehouse Architecture: Design multi-layer real-time data models, build and tune streaming ETL pipelines, and support continuous delivery of real-time business metrics and analytics.
• Kafka & Streaming Optimization: Maintain and optimize core Kafka streaming infrastructure. Diagnose and resolve online challenges including message backlogs, data skew, message loss, duplication, and partition tuning.
• Spark & Flink Operations: Develop, tune, and operate real-time Spark/Flink tasks to maximize computing resource utilization, throughput, and sub-second latency.
• Cross-Functional Collaboration: Partner with data product managers, analysts, and business stakeholders to translate complex business requirements into scalable, production-ready data pipelines.
• Data Quality & Governance: Establish data standardization practices, automated data quality monitoring, alert thresholds, and SLA governance protocols.

Required Experience & Qualifications

• Education: Bachelor’s degree or higher in Computer Science, Software Engineering, Data Science, or a related technical discipline.
• Work Experience: 3+ years of professional big data engineering experience in high-scale tech/internet environments with proven track records in real-time pipeline construction.

Core Technical Stack

• Languages: Proficiency in Python, Scala, or Java with solid Shell/Linux scripting capabilities.
• Streaming Infrastructure: Expert-level knowledge of Apache Kafka (partitioning strategies, consumer mechanisms, lag mitigation, deduplication).
• Compute & Processing: Strong hands‑on experience with Apache Spark (Spark SQL) and Apache Flink (Flink SQL) for streaming task optimization.
• Ingestion & CDC: Hands‑on experience with Change Data Capture (CDC) and Binlog real-time synchronization from operational databases.
• Cloud Ecosystems: Exposure to cloud-native platforms (Google Cloud Platform / BigQuery, Azure, Databricks, dbt).
• Languages & Communication: Professional working fluency in English (verbal and written) for cross‑border collaboration.

Preferred Qualifications

• Prior experience studying or working internationally or collaborating across cross-border remote tech teams.
• Hands‑on knowledge of real-time SLA governance, incident post-mortem processes, and automated alerting frameworks.