Senior Data Engineer Distributed Systems; GCP

Who we are:

Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 cities around the world, we are the AI technology solutions provider‑of‑choice to 4 out of 5 of the world’s biggest technology companies, as well as leading companies across financial services, insurance, technology, law, and medicine.

By combining advanced machine learning and artificial intelligence (ML/AI) technologies, a global workforce of subject matter experts, and a high‑security infrastructure, we’re helping usher in the promise of clean and optimized digital data to all industries. Innodata offers a powerful combination of both digital data solutions and easy‑to‑use, high‑quality platforms.

Our global workforce includes over 3,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel and Germany. We’re poised for a period of explosive growth over the next few years.

• Design, build, and optimize scalable data pipelines for batch and real‑time processing
• Develop and maintain event‑driven architectures for high‑throughput systems
• Ensure data reliability, performance, and low‑latency processing across distributed environments
• Collaborate with data scientists and application teams to enable analytics and AI use cases
• Implement best practices in performance tuning, monitoring, and cost optimization

• Advanced proficiency in Python for backend and large‑scale data processing
• Strong experience building and managing big data pipelines in production environments
• Hands‑on expertise with workflow orchestration tools such as Airflow or Google Cloud Composer
• Proven experience in batch and streaming data processing using:
  • Apache Spark
  • Apache Beam (Dataflow)
• Experience designing and operating event‑driven systems using Pub/Sub
• Strong understanding of distributed systems architecture and scalability patterns
• Experience managing globally distributed, low‑latency datasets
• Hands‑on experience with No
  
  SQL databases and/or Google Cloud Spanner
• Strong knowledge of system reliability, fault tolerance, and performance optimization

• Proficiency in Go, Java, or Scala
• Experience with Kafka or Flume for streaming ingestion
• Deep familiarity with the Google Cloud Platform ecosystem
• Experience with production monitoring, logging, and observability frameworks
• Exposure to high‑availability, multi‑region deployments

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