InMobi Advertising is a global technology leader helping marketers win the moments that matter. Our advertising platform reaches over 2 billion people across 150+ countries and turns real-time context into business outcomes, delivering results grounded in privacy-first principles. Trusted by 30,000+ brands and leading publishers, InMobi is where intelligence, creativity, and accountability converge. By combining lock screens, apps, TVs, and the open web with AI and machine learning, we deliver receptive attention, precise personalization, and measurable impact. Through Glance AI, we are shaping AI Commerce, reimagining the future of e-commerce with inspiration-led discovery and shopping. Designed to seamlessly integrate into everyday consumer technology, Glance AI transforms every screen into a gateway for instant, personal, and joyful discovery. Spanning diverse categories such as fashion, beauty, travel, accessories, home décor, pets, and beyond, Glance AI delivers deeply personalized shopping experiences. With rich first- party data and unparalleled consumer access, it harnesses InMobi's global scale, insights, and targeting capabilities to create high impact, performance driven shopping journeys for brands worldwide. Recognized as a Great Place to Work, and by MIT Technology Review, Fast Company's Top 10 Innovators, and more, InMobi is a workplace where bold ideas create global impact. Backed by investors including SoftBank, Kleiner Perkins, and Sherpalo Ventures, InMobi has offices across San Mateo, New York, London, Singapore, Tokyo, Seoul, Jakarta, Bengaluru and beyond.

At InMobi Advertising, you'll have the opportunity to shape how billions of users connect with content, commerce, and brands worldwide. To learn more, visit www.inmobi.com

Role Overview

We are hiring a Tech Lead / SDE IV to anchor and grow our Data Engineering capability within our Demand-Side Platform (DSP). This is a high-impact, technically hands-on leadership role at the intersection of real-time data infrastructure, programmatic advertising, and scalable backend systems. You will own the design and delivery of pipelines that power bidding intelligence, audience targeting, campaign analytics, and attribution — processing billions of bid-stream events daily. Alongside your data engineering mandate, you will architect and contribute to backend microservices that sit at the core of our DSP stack, including integrations with SSPs, ad exchanges, and identity resolution platforms. You will mentor a team of engineers, drive technical direction, and collaborate closely with product, ML, and growth functions to turn data into a true competitive advantage.

Key Responsibilities:

Data Stack:

▸ Design and own end-to-end data pipelines — batch and real-time — handling bid requests, win/loss events, impression logs, click streams, and conversion signals at scale.

▸ Build and maintain our data lakehouse architecture (ingestion → storage → serving layer) optimized for low-latency DSP analytics and ML feature generation.

▸ Define standards for data quality, lineage, observability, and SLA adherence across all data products.

▸ Own and evolve our StarRocks deployment for real-time analytical queries — schema design, ingestion patterns, and query optimisation for DSP reporting workloads.

▸ Drive FinOps discipline across the data platform — track compute and storage costs, enforce resource quotas, identify optimisation opportunities, and report on unit economics.

▸ Establish and lead Data Governance practices: metadata management, data cataloguing, access control policies, PII classification, and data retention standards compliant with GDPR and CCPA.

Backend Microservices:

▸ Contribute to and review the design of backend services that power DSP functionality — bid shading, pacing, budget management, and reporting APIs.

▸ Architect data contracts and event schemas between microservices, ensuring consistency across the bid request lifecycle.

▸ Champion best practices in API design, service reliability (SLOs, circuit breakers, retries), and observability (distributed tracing, structured logging, metrics).

▸ Collaborate with the bidder team on low-latency data reads (Aerospike, Cassandra, or similar) for real-time targeting signal lookups.

Technical Leadership

▸ Lead architecture reviews, set engineering standards, and drive adoption of best practices across the data and backend engineering teams.

▸ Mentor SDE II/III engineers through code reviews, design sessions, and pair programming; grow the next generation of technical leaders.

▸ Partner with ML engineers on the full model lifecycle — feature engineering pipelines, offline training data generation, experiment tracking, and model serving infrastructure.

▸ Translate complex business requirements (campaign KPIs, ROAS, viewability, brand safety) into robust technical designs.

▸ Own the technical roadmap for data infrastructure — capacity planning, migration strategies, and build vs. buy decisions.

Required Skills & Qualifications

Experience & Education

▸ 8+ years of software engineering experience, with at least 4 years focused on data engineering or large-scale data systems.

▸ Prior experience in ad-tech, programmatic advertising, or real-time bidding (RTB) environments strongly preferred.

▸ Experience in ML engineering — feature engineering, building offline training pipelines, or collaborating closely on model productionisation — is preferred.

▸ Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.

Data Engineering (Core)

▸ Deep expertise in distributed stream processing frameworks — Apache Kafka, Apache Flink, or Apache Spark Structured Streaming.

▸ Strong command of SQL and experience optimizing complex analytical queries at petabyte scale.

▸ Hands-on experience with real-time analytical databases, particularly StarRocks; familiarity with Snowflake or ClickHouse is a plus.

▸ Proficiency with workflow orchestration tools: Apache Airflow, Prefect, or Dagster.

▸ Solid understanding of data modelling — dimensional modelling, OBT patterns, and eventdriven schemas relevant to ad impression and attribution data.

▸ Familiarity with open table formats: Apache Iceberg, Delta Lake, or Apache Hudi.

Backend & Systems

▸ Proficiency in Python (primary) and/or Java/Scala for building production-grade services and data processing jobs.

▸ Experience designing and building RESTful APIs and/or gRPC-based microservices.

▸ Working knowledge of low-latency data stores (Aerospike, Cassandra) used for real-time lookups in the bidding path.

▸ Comfortable with containerised deployments on Kubernetes and CI/CD pipelines (GitHub Actions, ArgoCD, or similar).

SDE-IV _ Data Engineer