Staff Data Engineer

At Talkdesk, we are courageous innovators focused on redefining the customer experience, making the impossible possible for companies globally. We champion an inclusive and diverse culture representative of the communities in which we live and serve. And, we give back to our community by volunteering our time, supporting non-profits, and minimizing our global footprint. Each day, thousands of employees, customers, and partners all over the world trust Talkdesk to deliver a better way to great experiences.

We are recognized as a cloud contact center leader by many of the most influential research organizations, including Gartner and Forrester. With $498 million in total funding, a valuation of more than $10 Billion, and a ranking of #16 on the Forbes Cloud 100 list, now is the time to be part of the Talkdesk legacy to help accelerate our success in a new decade of transformational growth.

At Talkdesk, we embrace FAST, our fundamental operating principles that define who we are as an organization. These principles drive us to make the impossible possible. FAST: Focus + Accountability + Speed = Talkdesker.

• Focus: Focus time, energy and attention on what is most impactful for the business and thoughtful about how and when to partner with others.
• Accountability: Hold self and others accountable to meet commitments and drive results. Accept responsibility for successes and failures.
• Speed: Execute with agility and urgency. Act promptly, decisively, and without delay. Make good and timely decisions that keep the organization moving forward.
• Talkdesker: YOU

Purpose:

We are looking for a savvy Senior Data Engineer to join our growing team of Data experts. The hire will be responsible for expanding and optimizing our data pipeline architecture and data flow and collection for cross-functional teams and maintaining governance over our lakehouse. The Data Engineering team will partner with fellow software engineers to build data pipelines and solve data-related problems within the company.

Responsibilities:

• Develop, deploy, and maintain Big Data solutions that will ingest, process, and store the necessary data to power Talkdesk's business
• Design batch or streaming dataflows capable of processing large quantities of fast-moving unstructured data
• Monitoring dataflows and underlying systems, promoting the necessary changes to ensure scalable, reliable, and high-performance solutions 
• Work closely with the rest of Talkdesk's engineering to deliver world-class data-driven solutions

Required Skills:

• Strong understanding of distributed computing principles and distributed systems
• Proven experience in building datalake and/or lakehouse data architectures, integrating large volumes of data sourced from different sources predominantly in a real-time fashion
• Proficient in one or more 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
• Good 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

Nice to have / Pluses:

• Experience with NoSQL databases, such as MongoDB, Cassandra, ElasticSearch, or Redis;
• BS/MS Degree in Computer Engineering, Computer Science, Applied Math, or another engineering-related field
• Experience in Agile development methodology/Scrum
• Good understanding of Lambda and Kappa Architectures, along with their advantages and drawbacks
• Experience in containerization and orchestration technologies, including Docker and Kubernetes, to streamline application deployment and management.

Work Environment and Physical Requirements:

Primarily office-environment work, extended periods of sitting or standing, computer-based work. Limited lifting, and equipment usage limited to computer-related equipment (keyboards, mouse, etc.)