Roles & Responsibilities

Required and desired skills/qualifications:

• Desired candidate should be having around 5-9 years of experience.
• Have strong technical foundation with in-depth knowledge in Big Data Hadoop, Data Reporting, Data Design, Data Analysis, Data governance, Data integration and Data quality.
• Experience in monitoring, Tuning tasks on Cloudera distribution.
• Deep and extensive knowledge with HDFS, Spark, MapReduce, Hive, HBase, Sqoop, Yarn, Airflow.
• Thorough knowledge on Hadoop architecture and various components such as HDFS, Name Node, Data Node, Application Master, Resource Manager, Node Manager, Job Tracker, Task Tracker and MapReduce programming paradigm.
• Good understanding on Hadoop MR1 and MR2 (YARN) Architecture.
• Efficient in working with Hive data warehouse tool creating tables, data distributing by implementing Partitioning and Bucketing strategy, writing and optimizing the HiveQL queries.
• Good experience working with different Hadoop file formats like Sequence File, ORC, AVRO and Parquet.
• Experience in using modern Big-Data tools like SparkSQL to convert schema-less data into more structured files for further analysis. Experience in Spark Streaming to receive real time data and store the stream data into HDFS.
• Good Knowledge on Hadoop Cluster architecture and monitoring the cluster.
• In-depth understanding of Data Structure and Algorithms.
• Implemented in setting up standards and processes for Hadoop based application design and implementation.
• Experience in importing and exporting data using Sqoop from HDFS to Relational Database Systems and vice-versa.
• Experience in working on Avaloq data processing. Participation in multiple Avaloq Core Banking Platform implementations in various business / technical streams
• Good experience in CI/CD pipeline and working in Agile environment.
• Hands on experience with Real time streaming using Kafka, Spark streaming into HDFS.
• Developed analytical components using SparkSql and Spark Stream.
• Involved in converting Hive/SQL queries into Spark transformations using Spark SQL using Scala.
• Good knowledge streaming data using Kafka from multiple sources into HDFS.
• Knowledge of processing and analyzing real-time data streams/flows using Kafka and HBase.
• Proficient in all phases of software development including design, configuration, testing, debugging, implementation, release, and support of large-scale, Bank platform applications.

Tell employers what skills you have

Airflow
Data Analysis
Big Data
Hadoop
ETL
Data Integration
Data Quality
Data Governance
MapReduce
Data Design
Tuning
SQL
Debugging
Software Development