Senior Software Engineer – Platform Operations

DeepIntent is the leading healthcare marketing platform, purpose-built to help marketers plan, activate, and optimize data-driven campaigns with speed and precision. Trusted by the world’s top healthcare brands and their agencies, DeepIntent uniquely unites media, identity, and real-world clinical data to power privacy-safe, omnichannel marketing across every screen. Backed by patented technology and proven outcomes, DeepIntent’s platform delivers measurable audience quality and script lift at scale. Learn more at www.deepintent.com . What You’ll Do: We are looking for a Senior Software Engineer – Platform Operations based in Pune, India, who will play a key role in ensuring the reliability, performance, and operational excellence of DeepIntent's platform and data ecosystem. This role requires a strong engineering mindset with the ability to troubleshoot complex technical issues, understand distributed data architectures, and collaborate across Engineering, Product, Analytics, and Customer-facing teams to deliver timely and effective solutions. As part of the Operations organization, you will work closely with Engineering to support production systems, improve operational processes, and drive platform stability. The ideal candidate is a self-motivated problem solver who is passionate about learning new technologies, improving system reliability, and delivering exceptional customer outcomes through engineering excellence. Serve as the engineering interface between Customer-facing teams, Analytics, Product, and Engineering organizations. Partner with Platform Support, Client Success, and other customer-facing teams to investigate and resolve complex platform-related issues. Analyze application, API, and data pipeline issues to identify root causes and drive timely resolution. Develop and standardize operational tools, and interfaces to support analytical and operational use cases. Monitor data pipeline executions, investigate failures, and implement corrective and preventive actions. Implement operational best practices to improve platform reliability and efficiency. Collaborate with Software Engineers, Data Engineers, Machine Learning Engineers, Analysts, and Product teams to deliver scalable platform solutions. Act as a bridge between Engineering and Analytics teams to streamline issue resolution and improve operational effectiveness. Participate in production incident management, root cause analysis (RCA), post-incident reviews, and continuous improvement initiatives. Identify automation opportunities to reduce manual operational effort and improve platform monitoring and observability. Who You Are: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. 4+ years of professional software engineering or platform engineering experience. Strong proficiency in Java. Hands-on experience debugging Java applications in production environments. Strong analytical and problem-solving skills with the ability to troubleshoot complex technical issues across multiple systems. Proficient in writing and optimizing SQL queries and working with large-scale datasets. Experience working with distributed data pipelines and high-volume, high-velocity data processing systems. Experience supporting production applications in an L2/L3 Product Support or Technical Support environment. Good understanding of software engineering principles methodologies. Experience working with cloud platforms such as Google Cloud Platform (GCP) and/or Amazon Web Services (AWS). Strong communication and collaboration skills with the ability to work effectively with both technical and non-technical stakeholders. Proven ability to work with globally distributed teams, including teams based in the United States. Good understanding of application monitoring, logging, and incident management practices. Good to have experience investigating UI-related issues and browser-based debugging. Good to have knowledge of Python for automation, scripting, or operational tooling. Experience with Apache ecosystem technologies such as Spark, Airflow, Beam, Druid, Kafka, or similar distributed data processing frameworks is an added advantage. Experience with analytical databases such as BigQuery, ClickHouse, or similar large-scale data platforms is preferred. Demonstrated ability to take ownership, drive continuous improvement, learn new technologies quickly, and deliver high-quality solutions in a fast-paced environment. Comfortable working