Design and develop high performance and secured Databricks solutions using Python, Spark, PySpark, Delta tables, UDP and Kafka
Create high-quality technical documents including, data mapping, data processes, and operational support guides
Translate business requirements into data model design and technical solutions
Develop data ingest pipelines using Python, Spark & PySpark to support near real-time and batch ingestion processes
Maintain data lake and pipeline processes which includes troubleshooting issues, performance tuning and making data quality improvements
Work closely with technical leaders, product managers, and reporting team to gather functional and system requirements
Work in fast pace environment and perform effectively in an agile development environment

KNOWLEDGE AND SKILL REQUIREMENTS

Bachelor s degree in Computer Science or Information Systems, MCA or equivalent degree
Must have 2+ years of experience in developing applications using Python, Spark, PySpark, Java, Junit, Maven and its eco-system
Must have 2+ years of hands-on experience in AWS Databricks and related technologies like MapReduce, Spark, Hive, Parquet and AVRO
Good experience in end-to-end implementation of DW BI projects, especially in data warehouse and data mart developments
Extensive hands on RDD, Data frame and Dataset operations of Spark 3.x
Experience with design and implementation of ETL/ELT framework for complex warehouses/marts.
Knowledge of large data sets and experience with performance tuning and troubleshooting
Plus to have AWS Cloud Analytics experience in Lambda, Athena, S3, EMR, Redshift, Redshift spectrum
Must have RDBMS: Microsoft SQL Server, Oracle, MySQL
Understanding of Data architecture, replication, and administration
Experience in working with real-time data ingestion with any streaming tool
Debugging skills to troubleshoot production issues
Comfortable working in a team environment
Hands on experience with SQL
Ability to identify problems, and effectively communicate solutions to peers and management

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