Data Engineer II- C360, Hyderabad

What we do 

At WBD, the Consumer 360 team is made up of data engineers, software engineers, data scientists, and ML engineers. We ingress, analyze, and organize Big Data about our current and prospective customers—how they live, the content they watch, what they prefer, how they act, how they think—and we enrich this with vast libraries of available demographic and other information, all to empower more effective, less intrusive, and more targeted advertising, boost engagement, drive new subscriptions, and reduce churn.  

What you’ll Do 

• Build software across our entire cutting-edge data platform, including event driven and batch data processing, storage, and serving through various data integration techniques such as APIs, Lambda, File Feeds etc. 

• Develop and maintain data integrations including direct digital marketing, social channels, etc. 

• Ingest, process massive campaign datasets to analyze the campaign performance. 

• Work closely with data architects, stream processing specialists, API developers, our DevOps team, and analysts to design systems which can scale elastically.  

• Work closely with data analysts and business stake holders to make data easily accessible and understandable to them. 

• Ensure data quality by implementing re-usable data quality frameworks. 

• Work closely with various other data engineering teams to roll out new capabilities. 

• Work closely with AI/ML team to operationalize and utilize models for business needs. 

• Develop and enforce data engineering, security, data quality standards through automation. 

• Participate in on-call rotations 

What you’ll Need 

• Bachelor’s degree in computer science or similar discipline. 

• 2+ years of experience in software and data engineering 

• Ability and willingness to learn any modern technologies and apply them at work to stay ahead of the curve. 

• Expertise in at least a few programming languages - Java, Scala, Python or similar. 

• Expertise in building and managing large volume data processing (both streaming and batch) platform is a must. 

• Expertise with cloud data warehouses, such as Databricks, Snowflake or Redshift. 

• Expertise in SQL, Spark SQL, Hive etc. 

• Expertise in stream processing systems such as Kafka, Kinesis, Pulsar or Similar 

• Expertise in building micro services and managing containerized deployments, preferably using Kubernetes. 

• Expertise in distributed data processing frameworks such as Apache Spark, Flink or Similar. 

• Cloud (AWS) experience is preferred.