Lead Data Engineer

Job Description

About MoEngageMoEngage is an Intelligent customer engagement platform, built for customer-obsessed marketers and product owners. We enable hyper-personalization at scale across multiple channels like mobile push, email, in-app, web push, on-site massages, and SMS. With AI-powered automation and optimization, brands can analyze audience behavior and engage consumers with personalized communication at every touchpoint across their lifecycle.Fortune 500 brands and Enterprises across 35 countries such as Deutsche Telekom, Samsung, Ally Financial, Vodafone, and McAfee along with internet-first brands such as Flipkart, Ola, OYO, Bigbasket, and Tokopedia use MoEngage to orchestrate their cross-channel campaigns and engage efficiently with their customers sending 50 billion messages to 500 million consumers every month!Our vision is to build the world s most trusted customer engagement platform for the mobile-first world.We promise to care about your customers as much as you do. And that justifies our top ratings for service and support in Gartner Magic Quadrant, Gartner Peer Insights, and G2 Summer Reports. We have also been recognized as one of the 25 Highest Rated Private Cloud Computing Companies To Work For in a list released by Battery Ventures, a global investment firm based on the employee feedback on Glassdoor where employees reported the highest levels of satisfaction at work during the first six months of the pandemic. About Segmentation Team :Segmentation team is one of the core teams at MoEngage, responsible for analysing billions of events per month generated by millions of users, and building real-time query capabilities to power the most advanced user profiling engine available in the industry. As a member of the segmentation team, you will be working on some of core distributed computing concepts as well as challenging CS problems, to write code that processes Terabytes of data in minutes. You get first hand experience of handling data at scale. You get to work on building and scaling the latest segmentation tech stack which involves components like Presto, S3, Data Cataloguing, Stream Processing etc.As part of the Segmentation team at MoEngage , here are some things you can expect from this role:

• Take ownership and be responsible for what you build, and for all crucial architectural decisions in the team
• Work with A players (some of the best talents in the country), and expedite your learning curve and career growth
• Make in India and build for the world at the scale of 500M active users, which no other internet company in the country has seen
• Learn together from different teams on how they scale to millions of users and billions of messages.
• Revamp an existing Elasticsearch based architecture to a new scalable distributed storage system, with capabilities to process TeraBytes of data in minutes or seconds
• Explore the latest trends in technology like data warehousing, Spark, Samza, Flink, Airflow etc and share with the team
• Current Tech Stack - AWS (S3, Athena, Glue), Yarn + Spark, Apache Kafka Ecosystem (Kafka, Connect, Streams), Presto, Airflow, Python, Java, K8s

Skill Requirements

• Bachelor or Masters Degree with 6+ years of proven experience in handling large infrastructure and distributed systems
• Expert in Java related technologies and frameworks
• Familiarity with at least one of the cloud computing infrastructure - GCP / Azure / AWS
• Expert in Data Warehousing Technologies (atleast 2+ years of experience)
• Must have good experience working with Presto and Data Cataloguing Systems (Glue, Hive Metastore etc)
• Experience in python is a good to have.

At MoEngage, we are passionate about our team and technology - see below to know more about us and technology. Tech @MoEngage | Scale @MoEngage | Life @MoEngage We handle more than a billion messages everyday. Rest assured, you will be surrounded by really smart and passionate people as we scale much more to build a world class technology team.,

Keyskills :
global investmentprivate cloudoptimization strategiesjavadata warehousinginformaticagcpapache kafkauser profilingcustomer engagementhivedistributed storagecloud computingawspythonsqlola