Seeking a Data Engineer to join Mobile Advertising Platform engineering team. Responsibilities include designing and building scalable data platforms and ultra-low-latency data pipelines processing billions of mobile advertising events daily, including ad requests, impressions, clicks, installs, conversions, and auction logs. Architect real-time campaign pacing, budget delivery, and fraud detection systems using Java, Kafka, Spark Streaming, Hadoop, Snowflake, and AWS. Develop backend services and GenAI-powered analytics agents. Collaborate with cross-functional teams and participate in Agile processes. Requirements: 1-5+ years in Java backend development and data engineering, strong fundamentals in CS, experience with distributed data pipelines and Mobile AdTech platforms, knowledge of RTB, OpenRTB, DSP/SSP, mobile SDK tracking, attribution, mobile identity solutions, bid optimization, and fraud detection. Experience with GenAI applications, CI/CD, Docker, Kubernetes, and monitoring tools preferred. Bachelor’s degree in engineering or equivalent required. Hybrid work schedule with 3 days in office and 2 days remote. Benefits include parental leave, healthcare insurance, broadband reimbursement, snacks, and catered lunches.
What you'll do
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Design and build highly scalable data platforms processing billions of mobile advertising events with low latency and high availability
Design and build ultra-low-latency, high-throughput data pipelines for mobile event funnel including OpenRTB bid request/response logging, auction analytics, and reporting
Architect real-time campaign pacing and budget delivery systems with bid optimization reacting to live auction signals
Architect and implement real-time streaming pipelines to ingest, process, and analyze billions of advertising events
Design and optimize scalable ETL/ELT pipelines and data models for Mobile AdTech use cases such as campaign reporting, attribution, audience segmentation, fraud detection, and revenue analytics
Design large-scale Invalid Traffic (IVT) and ad fraud detection systems using rules-based and ML-driven detection
Design and develop GenAI-powered agents for analytics, operations, and data enrichment
Design systems that are highly available, fault tolerant, and optimized for low latency and high throughput
Collaborate closely with cross-functional teams to improve platform scalability, reliability, performance, and customer experience
Work with Product Managers to define and implement new analytics capabilities and platform features
Participate in Agile/Scrum ceremonies including sprint planning, backlog grooming, estimation, retrospectives, and release planning
Perform architecture discussions, design reviews, and peer code reviews while promoting software engineering best practices
Requirements
1–5+ years of professional experience in Java backend development and data engineering
Strong computer science fundamentals including data structures, algorithms, distributed systems, and software design principles
Hands-on experience developing scalable backend services using Java, REST APIs, JDBC, and relational databases
Strong experience building distributed data pipelines using Spark, Kafka, Hadoop, Snowflake, SQL, and AWS
Experience designing and optimizing large-scale analytical data platforms for Mobile AdTech using Java, Spark, Kafka, Snowflake, SQL, and AWS
Strong understanding of real-time event processing, distributed data systems, and data warehouse architectures
Familiarity with distributed query engines, modern data lake technologies, and high-performance analytical databases (e.g., Trino, Presto, ClickHouse, Apache Iceberg, Delta Lake, or Apache Hudi) is an added advantage
Experience processing high-volume streaming data using Spark Streaming, Kafka Streams, or similar technologies
Good understanding of data warehousing, dimensional modeling, ETL/ELT design, and distributed computing concepts
Experience working with Mobile AdTech platforms or digital advertising ecosystems is highly preferred
Knowledge of Real-Time Bidding (RTB), OpenRTB protocol, and Mobile DSP/SSP/Ad Exchange architecture
Familiarity with mobile SDK event tracking and Mobile Measurement Partner (MMP) integrations
Understanding of attribution methodologies (click-through, view-through, multi-touch based attribution)
Knowledge of mobile identity solutions (IDFA, GAID, IDFV) and privacy landscape
Experience with campaign pacing, bid optimization, and budget delivery algorithms
Background in ad fraud/IVT detection (click spam, install fraud, SDK spoofing)
Experience building production-grade GenAI applications including LLM integration and orchestration frameworks
Prompt engineering and optimization skills
AI evaluation, observability, agents, and workflow automation experience
Experience with CI/CD pipelines, Docker, Kubernetes, and cloud-native application development
Experience with monitoring and observability tools such as Grafana, Prometheus, Datadog, or AWS
Strong debugging and troubleshooting skills in distributed environments
Ability to learn new technologies quickly and independently
Excellent verbal and written communication skills
Strong interpersonal skills for collaboration across teams
Bachelor’s degree in engineering or equivalent from a recognized institute/university
