Specialist - Data Platform Engineering

Organizations everywhere struggle under the crushing costs and complexities of solutions that promise to simplify their lives. To create a better experience for their customers and employees. To help them grow. Software is a choice that can make or break a business. Create better or worse experiences. Propel or throttle growth. Business software has become a blocker instead of ways to get work done.

There's another option. Freshworks. With a fresh vision for how the world works.


At Freshworks, we build uncomplicated service software that delivers exceptional customer and employee experiences. Our enterprise-grade solutions are powerful, yet easy to use, and quick to deliver results. Our people-first approach to AI eliminates friction, making employees more effective and organizations more productive. Over 72,000 companies, including Bridgestone, New Balance, Nucor, S&P Global, and Sony Music, trust Freshworks customer experience (CX) and employee experience (EX) software to fuel customer loyalty and service efficiency. And, over 4,500 Freshworks employees make this possible, all around the world.

Fresh vision. Real impact. Come build it with us.

About the Role

We are looking for a Data Platform Engineer (IC2) to build and operate scalable, reliable, and high-performance data platforms. In this role, you will develop streaming and batch data pipelines, manage Databricks environments, and support our event-driven data infrastructure using Kafka and Kafka Connect.

This is an excellent opportunity for engineers with a strong foundation in distributed data processing who want to work on modern data engineering technologies at scale.

Key Responsibilities

• Develop, maintain, and optimize batch and streaming data pipelines using Apache Spark and Apache Flink.
• Build scalable ETL/ELT workflows for processing large datasets.
• Manage and maintain Databricks workspaces, clusters, jobs, notebooks, and workflows.
• Monitor, troubleshoot, and optimize Databricks jobs for performance and cost efficiency.
• Work with Apache Kafka for event-driven data processing and streaming applications.
• Configure, deploy, and troubleshoot Kafka Connect connectors for integrating various data sources and sinks.
• Ensure data reliability through monitoring, alerting, and operational best practices.
• Collaborate with software engineers, platform engineers, and data consumers to design robust data solutions.
• Participate in production support, incident response, and root cause analysis.
• Contribute to automation, documentation, and continuous improvement of the data platform.

What You'll Learn

• Design and operate enterprise-scale data platforms.
• Build high-throughput streaming applications using Spark and Flink.
• Manage production Databricks environments efficiently.
• Develop expertise in Kafka ecosystem components, including Kafka Connect.
• Work with modern cloud-native data engineering technologies and best practices.

Success Metrics

• Deliver reliable and scalable batch and streaming pipelines.
• Maintain high platform availability and operational excellence.
• Optimize job performance and infrastructure costs.
• Improve data quality, observability, and platform automation.
• Collaborate effectively across engineering teams to deliver business value.
  
  

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 3–4 years of experience in software engineering or data engineering.
• Strong programming skills in Java, Scala, or Python.
• Hands-on experience with Apache Spark for large-scale data processing.
• Knowledge of Apache Flink for stream processing.
• Experience working with Databricks, including cluster management and job orchestration.
• Good understanding of Apache Kafka, including topics, partitions, producers, and consumers.
• Familiarity with Kafka Connect and connector deployment.
• Understanding of distributed systems, data pipelines, and streaming architectures.
• Experience with Git and CI/CD practices.
• Strong problem-solving and debugging skills.

Preferred Qualifications

• Experience with Delta Lake and Lakehouse architecture.
• Knowledge of cloud platforms such as AWS, Azure, or GCP.
• Familiarity with Airflow, Argo Workflows, or similar orchestration tools.
• Experience with monitoring tools such as Prometheus and Grafana.
• Understanding of Kubernetes and containerized deployments.
• Knowledge of SQL optimization and data modeling.
  
  

At Freshworks, we have fostered an environment that enables everyone to find their true potential, purpose, and passion, welcoming colleagues of all backgrounds, genders, sexual orientations, religions, and ethnicities. We are committed to providing equal opportunity and believe that diversity in the workplace creates a more vibrant, richer environment that boosts the goals of our employees, communities, and business. Fresh vision. Real impact. Come build it with us.