Who We Are
Verve has created a more efficient and privacy-focused way to buy and monetize advertising. Verve is an ecosystem of demand and supply technologies fusing data, media, and technology together to deliver results and growth to both advertisers and publishers–no matter the screen or location, no matter who, what, or where a customer is. With 30 offices across the globe and with an eye on servicing forward-thinking advertising customers, Verve’s solutions are trusted by more than 90 of the United States’ top 100 advertisers, 4,000 publishers globally, and the world’s top demand-side platforms. Learn more at www.verve.com.
Who You Are
We're looking for a Senior Data Engineer to join our Data Processing team at Verve. This team is responsible for designing and maintaining scalable, real-time, and batch data processing pipelines that enable high-quality insights and analytics. The Data Processing team works closely with the Data Analytics and Data Science teams to ensure efficient data flows across the organization.
In this role, you'll focus on developing and optimizing data processing workflows, ETL pipelines, and streaming solutions. Precision, efficiency, and high-quality deliverables are essential, and you'll report to the Engineering Manager, Data Processing.
If you are passionate about working with big data technologies, real-time data processing, and optimizing large-scale ETL workflows, we’d love to hear from you!
This is a hybrid position with three days per week in our Bengaluru office.
What You Will Do
Domain Expertise:
Design, develop, and maintain scalable, efficient, and cost-effective data pipelines for real-time and batch data processing.
Build high-performance ETL workflows leveraging Kafka, Apache Spark, and Scala.
Implement best practices for data modeling, storage, and retrieval, ensuring high availability and reliability.
Work with GCP-based data services, including BigQuery, Dataflow, and Cloud Storage.
Optimize the performance and cost efficiency of data processing jobs.
Data Processing & Engineering
Architect and implement scalable streaming and batch processing solutions.
Develop real-time data processing pipelines using Kafka and Apache Spark Structured Streaming.
Ensure the stability and reliability of high-volume data ingestion pipelines.
Write clean, testable, and efficient code using Scala.
Ensure compliance with data privacy and security best practices.
Collaborative Work
Work closely with Data Analytics and Data Science teams to ensure data is processed, stored, and accessed efficiently.
Collaborate with the Data Analytics team to provide structured data for data warehouses, reporting APIs, and UIs.
Support the Data Science team by ensuring high-quality data availability for machine learning models.
Work cross-functionally with engineering and product teams to design end-to-end data solutions.
Coordinate with global teams in different time zones to deliver projects successfully.
Extend optimized solutions to sister companies within Verve Group.