Delivery Project Lead

Job DescriptionJob Summary –ResponsibilitiesDevelop and maintain data platforms using Python, Spark, and PySpark.Handle migration to PySpark on AWS.Design and implement data pipelines.Work with AWS and Big Data.Produce unit tests for Spark transformations and helper methods.Create Scala/Spark jobs for data transformation and aggregation.Write Scaladoc-style documentation for code.Optimize Spark queries for performance.Integrate with SQL databases (e.g., Microsoft, Oracle, Postgres, MySQL).Understand distributed systems concepts (CAP theorem, partitioning, replication, consistency, and consensus).SkillsProficiency in Python, Scala (with a focus on functional programming), and Spark.Familiarity with Spark APIs, including RDD, DataFrame, MLlib, GraphX, and Streaming.Experience working with HDFS, S3, Cassandra, and/or DynamoDB.Deep understanding of distributed systems.Experience with building or maintaining cloud-native applications.Familiarity with serverless approaches using AWS Lambda is a plusYears of experience needed –Technical SkillsScreening Questions:Process SkillsAbout MphasisMphasis applies next-generation technology to help enterprises transform businesses globally. Customer centricity is foundational to Mphasis and is reflected in the Mphasis’ Front2Back™ Transformation approach. Front2Back™ uses the exponential power of cloud and cognitive to provide hyper-personalized (C=X2C2TM=1) digital experience to clients and their end customers. Mphasis’ Service Transformation approach helps ‘shrink the core’ through the application of digital technologies across legacy environments within an enterprise, enabling businesses to stay ahead in a changing world. Mphasis’ core reference architectures and tools, speed and innovation with domain expertise and specialization are key to building strong relationships with marquee clients.