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Job Description

Talkdesk is seeking a Senior Data Engineer to join their growing team of Data experts. Talkdesk is known for redefining customer experience and fostering an inclusive culture.

The Senior Data Engineer will be responsible for expanding and optimizing the data pipeline architecture, data flow, and collection for cross-functional teams, as well as maintaining governance over the lakehouse. The Data Engineering team will collaborate with software engineers to build data pipelines and solve data-related problems within the company.

Responsibilities:

  • Develop, deploy, and maintain Big Data solutions for data ingestion, processing, and storage.
  • Design batch or streaming dataflows for processing large quantities of fast-moving unstructured data.
  • Monitor dataflows and underlying systems, implementing changes for scalable, reliable, and high-performance solutions.
  • Collaborate with Talkdesk’s engineering team to deliver data-driven solutions.

Requirements:

  • Strong understanding of distributed computing principles and distributed systems.
  • Experience in building datalake and/or lakehouse data architectures.
  • Proficiency in languages like Java, Kotlin, or Scala (Python developers willing to work on JVM are also welcome).
  • Experience with messaging systems such as Kafka, RabbitMQ, or ActiveMQ.
  • Experience with distributed processing engines such as Flink, Spark, and/or Kafka Streams.
  • Knowledge of analytical tools such as Trino, Dremio, Impala or similar.
  • Experience with table formats such as Hive, Iceberg, Delta Lake, Hudi or similar.
  • Experience with relational databases, including data modeling, scalability strategies, and performance analysis.
  • Experience with cloud environments such as AWS, Azure, or Google Cloud.
  • At least 4 years of relevant professional experience.
  • Strong written and verbal English communication skills.

The role offers:

  • Opportunity to work with a growing team of data experts at Talkdesk.
  • Chance to contribute to world-class data-driven solutions.
  • A hybrid work model.
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