Build data systems and pipelines using Apache Flink (or similar) pipelines.
Understand various raw data input formats, build consumers on Kafka/ksqldb for them and ingest large amounts of raw data into Flink and Spark.
Conduct complex data analysis and report on results.
Build various aggregation streams for data and convert raw data into various logical processing streams.
Build algorithms to integrate multiple sources of data and create a unified data model from all the sources.
Build a unified data model on both SQL and NO-SQL databases to act as data sink.
Communicate the designs effectively with the fullstack engineering team for development.
Explore machine learning models that can be fitted on top of the data pipelines.

Mandatory Qualifications Skills:





Deep knowledge of Scala and Java programming languages is mandatory
Solid background in streaming data frameworks (Apache Flink, Apache Spark) is mandatory
Good understanding and hands on skills on streaming messaging platforms such as Kafka
Familiarity with R, C and Python is an asset
Analytical mind and business acumen with strong math skills (e.g. statistics, algebra)
Problem-solving aptitude
Excellent communication and presentation skills Skills:- Data engineering, apache flink, kafka, flink, data analysis, non sql, Apache Kafka, Spark, Apache Spark, Scala and Java

📌 Data Engineer_1 (Mumbai)
🏢 Mgneto Resource Management
📍 Mumbai