SDE IV - Data Engineer at InMobi Advertising | AdTechTalent
Programmatic10 months agoOn-site
InMobi Advertising
SDE IV - Data Engineer
data engineeringprogrammaticreal-time biddingDSPApache KafkaApache FlinkApache SparkSQLStarRocksPythonJavaScalamicroservicesKubernetesCI/CDmachine learningfeature engineeringdata pipelinesbackendad-tech
Key details
Salary
Not specified
Employment type
Full-time
Seniority
Lead
Years experience
5-10
Location
Lucknow, India
Full job description
InMobi Advertising is hiring a Tech Lead / SDE IV to lead and grow Data Engineering within the Demand-Side Platform (DSP). The role involves designing and delivering scalable data pipelines for bidding intelligence, audience targeting, campaign analytics, and attribution processing billions of events daily. Responsibilities include building and maintaining data lakehouse architecture, managing real-time analytical databases (StarRocks), enforcing data governance and FinOps, and contributing to backend microservices for DSP functionality. The candidate will lead technical teams, mentor engineers, collaborate with ML and product teams, and own the technical roadmap. Required skills include 8+ years software engineering with 4+ years in data engineering, experience in ad-tech or programmatic advertising, expertise in distributed stream processing (Kafka, Flink, Spark), SQL, real-time databases, workflow orchestration, Python/Java/Scala programming, microservices, low-latency data stores, Kubernetes, and CI/CD. Strong leadership and communication skills are essential. Location: Lucknow, India.
What you'll do
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
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Build and maintain data lakehouse architecture 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 StarRocks deployment for real-time analytical queries including schema design, ingestion patterns, and query optimisation
Drive FinOps discipline across the data platform by tracking compute and storage costs, enforcing resource quotas, identifying optimisation opportunities, and reporting on unit economics
Establish and lead Data Governance practices including metadata management, data cataloguing, access control policies, PII classification, and data retention standards compliant with GDPR and CCPA
Contribute to and review the design of backend services powering DSP functionality such as 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
Lead architecture reviews, set engineering standards, and drive adoption of best practices across data and backend engineering teams
Mentor SDE II/III engineers through code reviews, design sessions, and pair programming
Partner with ML engineers on the full model lifecycle including 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 including capacity planning, migration strategies, and build vs. buy decisions
Requirements
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
Deep expertise in distributed stream processing frameworks (Apache Kafka, Apache Flink, 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, Dagster)
Solid understanding of data modelling (dimensional modelling, OBT patterns, event-driven schemas relevant to ad impression and attribution data)
Familiarity with open table formats (Apache Iceberg, Delta Lake, Apache Hudi)
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)
Demonstrated experience leading technical squads or functioning as a technical anchor on cross-functional projects
Strong written and verbal communication skills; ability to translate technical complexity for nonengineering stakeholders
Track record of driving projects from ambiguous requirements to production with high engineering quality
Continuous learning and career progression through the InMobi Live Your Potential programEqual Employment Opportunity employerReasonable accommodations for qualified individuals with disabilities
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