Engineering Manager - Data Engineering
Mumbai, INDIA
6d ago
source : TimesJobs

Engineering Manager - Data Engineering Mumbai, Maharashtra 1. Engineering Leadership Full time About the Role At Hotstar, we have over 100 million users and capture close to a billion click stream messages daily.

The engineering team at Hotstar is at the centre of the action and is responsible for creating unmatched user experience.

Our engineers solve real life complex problems and create compelling experiences for our customers. As a lead engineer in the Data Infrastructure team, you will build platforms and tools that churn through, process & analyze petabytes of data and lead a robust team You will work on technologies (such as Apache Kafka, Apache Spark, Aerospike, Redshift and such ) to build a scalable infrastructure that delivers recommendations to our users in real-time.

The pace of our growth is incredible if you want to tackle hard and interesting problems at scale, and create an impact within an entrepreneurial environment, join us! Your Key Responsibilities You will work closely with Software Engineers & ML engineers to build data infrastructure that fuels the needs of multiple teams, systems and products You will automate manual processes, optimize data-delivery and build the infrastructure required for optimal extraction, transformation and loading of data required for a wide variety of use-cases using SQL / Spark You will build stream processing pipelines and tools to support a vast variety of analytics and audit use-cases You will continuously evaluate relevant technologies, influence and drive architecture and design discussions You will work in cross-functional team and collaborate with peers during entire SDLC What to Bring BE / B.

Tech / BS / MS / PhD in Computer Science or a related field (ideal) Led a team in the past Minimum 4 years of work experience building data warehouse and BI systems Strong Java skills Experience in either Go or Python (plus to have) Experience in Apache Spark, Hadoop, Redshift, Athena Strong understanding of database and storage fundamentals Experience with the AWS stack Ability to create data-flow design and write complex SQL / Spark based transformations Experience working on real time streaming data pipelines using Spark Streaming or Storm

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