2 months ago
Pune, IndiaEntry Level / Mid Level
Responsibilities
- Design and build highly scalable, low-latency data platforms and streaming pipelines processing billions of mobile advertising events.
- Develop pipelines and analytics for RTB auctions, campaign pacing, bid optimization, attribution, audience segmentation, fraud detection, and revenue reporting.
- Build backend Java services, REST APIs, and reporting systems supporting DSP bidding logic and campaign management.
- Design large-scale invalid traffic and ad fraud detection systems using rules-based and machine-learning-driven methods.
- Develop GenAI-powered agents and workflow automation for analytics, operations, and data enrichment.
- Ensure systems are highly available, fault tolerant, scalable, and optimized for throughput and latency.
- Collaborate with product managers, ML engineers, data scientists, backend engineers, and customer-facing teams.
- Participate in architecture discussions, design reviews, code reviews, Agile/Scrum ceremonies, and software engineering best practices.
Requirements
- Bachelor’s degree in engineering or an equivalent degree.
- 1–5+ years of professional experience in Java backend development and data engineering.
- Strong knowledge of data structures, algorithms, distributed systems, software design, data warehousing, dimensional modeling, and ETL/ELT design.
- Hands-on experience with Java, REST APIs, JDBC, relational databases, SQL, Spark, Kafka, Hadoop, Snowflake, and AWS.
- Experience building high-volume streaming systems with Spark Streaming, Kafka Streams, or similar technologies.
- Experience designing analytical data platforms and optimizing SQL and query performance.
- Experience with Mobile AdTech, RTB, OpenRTB, DSP/SSP/ad exchange architecture, mobile SDK events, MMP integrations, attribution, mobile identity, campaign pacing, bid optimization, or ad fraud detection is preferred.
- Experience building production-grade GenAI applications involving LLM integration, prompt engineering, evaluation, observability, agents, and workflow automation.
- Familiarity with Trino, Presto, ClickHouse, Apache Iceberg, Delta Lake, or Apache Hudi is advantageous.
- Experience with CI/CD, Docker, Kubernetes, cloud-native applications, and monitoring tools such as Grafana, Prometheus, Datadog, or AWS is preferred.
- Strong debugging, troubleshooting, communication, collaboration, and independent learning skills.
Benefits
- Hybrid work schedule with three days in the office and two days working remotely.
- Paternity and maternity leave.
- Healthcare insurance.
- Broadband reimbursement.
- Kitchen stocked with healthy snacks and drinks and catered lunches when working in the office.
Tech Stack
Apache HadoopApache KafkaApache SparkAWSClickHouseDatadogDockerGrafanaJavaKubernetesPrestoPrometheusSnowflakeSQL
Categories
BackendData Engineering
About PubMatic
PubMatic builds a sell-side programmatic advertising platform that helps digital publishers and commerce media networks monetize display, mobile, video, and in‑app inventory by connecting them with DSPs and buyers. Its business model centers on fees from real-time ad auctions and related services, including RTB, yield optimization, and AI-driven decisioning. Founded in 2006, the company is headquartered in Redwood City, California, and is listed on NASDAQ under the ticker PUBM.