Job Description

'Minimum 0-3 years of Data Engineering experience

Proven experience in in SQL, Spark, Hadoop ecosystem

Have worked on multiple TBsof data volume from ingestion to consumption

Work with business stakeholders to identify and document high impact business problems and potential solutions

Good understanding of Data Lake/Lakehouse architecture and experience/exposure to Hadoop (cloudera, hortonworks) and/or AWS
Work on end-to-end data lifecycle from Data Ingestion, Data Transformation and Data Consumption layer. Versed with API and its usability
A suitable candidate will also be proficient in Spark, Spark Streaming, hive, SQLs

A suitable candidate will also demonstrate experience with big data infrastructure inclusive of MapReduce, Hive, HDFS, YARN, HBase, Oozie, etc.

The candidate will additionally demonstrate substantial experience and a deep knowledge of relational databases.

Good skills in technical debugging of the code in case of issues. Also, working with git for code versioning

Creating Technical Design Documentation of the projects/pipelines

Secondary Responsibilities :

'Ability to work independently and handle your own development effort.
Excellent oral and written communication skills Learn and use internally available analytic technologies
Identify key performance indicators and create educational/deliverables path to achieve the same
Use educational background in data engineering and perform data mining analysis
Work with BI analysts/engineers to create prototypes
Engage in the delivery and presentation of solutions