Opportunity at
InMobiSDE II - Data Engineer
InMobi is a global technology enterprise focused on agentic commerce and advertising, utilizing machine learning, generative AI, and data to connect brands with target audiences. The…
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About This Role
InMobi is a global technology enterprise focused on agentic commerce and advertising, utilizing machine learning, generative AI, and data to connect brands with target audiences. The organization operates ecosystems including InMobi Advertising and the consumer platform Glance. The Demand-Side Platform (DSP) division is currently hiring an SDE II - Data Engineer to design, operate, and scale data pipelines that power programmatic advertising campaigns, audience targeting, attribution, and analytics. This position…
Job Description
InMobi is a global technology enterprise focused on agentic commerce and advertising, utilizing machine learning, generative AI, and data to connect brands with target audiences. The organization operates ecosystems including InMobi Advertising and the consumer platform Glance. The Demand-Side Platform (DSP) division is currently hiring an SDE II - Data Engineer to design, operate, and scale data pipelines that power programmatic advertising campaigns, audience targeting, attribution, and analytics.
This position requires a practitioner capable of managing both batch and streaming information streams, utilizing cloud data platforms, distributed processing frameworks, and analytical storage solutions. The selected candidate will partner closely with product, machine learning, and backend engineering teams to deliver robust data infrastructure supporting DSP operations. The ideal candidate possesses solid core competencies in SQL, Python, and distributed data processing, along with a readiness to address high-volume event stream challenges, data reliability, and performance enhancements.
Responsibilities
- Design, maintain, and scale batch and streaming pipelines to handle event data such as conversions, clicks, impressions, and bid requests
- Construct data ingestion and transformation workflows utilizing Python, SQL, Apache Spark, and PySpark
- Contribute to data lakehouse architectures across serving, storage, ingestion, and transformation layers
- Incorporate schema validation, error handling, monitoring, and quality checks to guarantee accuracy
- Support query optimisation and data modelling for reporting and analytical needs
- Operate distributed processing tools including Apache Kafka, Apache Spark, and PySpark
- Build and support streaming workflows for event-driven information while focusing on reliability and freshness
- Investigate production issues, troubleshoot bottlenecks, and resolve pipeline failures
- Develop and optimise table structures, partitioning strategies, and SQL queries for cloud-based platforms
- Schedule and monitor data pipelines using workflow orchestration tools like Apache Airflow
- Participate in code reviews, technical discussions, testing, and deployment processes
Requirements
- Two to five years of professional experience in data engineering, big data development, or software engineering
- Demonstrated background in building and maintaining production-level data pipelines
- Proficiency in Python programming
- Solid command of SQL including aggregations, joins, query optimisation, and data transformations
- Practical experience with distributed data processing frameworks such as Apache Spark or PySpark
- Familiarity with ETL and ELT pipeline development
- Understanding of streaming data concepts and batch processing
Qualifications
- Bachelor's or Master's degree in Engineering, Computer Science, or a related technical discipline
- Prior exposure to ad-tech, real-time bidding, programmatic advertising, or event-driven systems
- Familiarity with workflow orchestration tools like Dagster, Prefect, or Apache Airflow
- Knowledge of data modelling, schema evolution, partitioning, and data quality practices
- Experience with messaging and streaming technologies such as Apache Kafka
- Exposure to cloud data services on AWS, GCP, or Azure
- Familiarity with analytical databases, data lakes, or lakehouse architectures
- Experience with technologies like Delta Lake, Apache Iceberg, Apache Hudi, StarRocks, or ClickHouse
- Knowledge of Java or Scala
- Basic understanding of microservices, REST APIs, and event-driven architectures
- Exposure to Docker, Kubernetes, and CI/CD tools
- Experience partnering with machine learning teams on training data pipelines or feature engineering
Core Skills
Frequently Asked Questions
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What is the employment type for the SDE II - Data Engineer role?
The posting specifies that this is a full-time position.
Where is this job located?
The job posting does not specify a location.
What is the remote work policy for this role?
The source posting states that the remote status is on-site.
What salary does InMobi offer for this position?
The salary is not stated in the job posting.
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