[AIT] Senior Data Engineer (MAX 3735)

​Duration: 12 months

No. of Role: 1

Monthly Salary: $7000 – $9000

Role:Data Engineer

Job Level: More than 10 years of relevant experience (L4)

Project: Data Lake Projects

Key Skills: Hadoop , Data Lake, SQL , Cloudera, Informatica

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Job Objectives:

Manage Hadoop cluster in across all 4 environments (SIT, UAT, PROD and DR)

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Key Responsibilities:

• Design, develop, and implement data processing pipelines to process large volumes of structured and unstructured data

• Should have good knowledge and working experience in Database and Hadoop (Hive, Impala, Kudu).

• Should have good knowledge and working experience in scripting using (Shell script, awk programming, quick automation to integrating any third party tools), BMC monitoring tools
  Good understanding and knowledge in Data Modelling area using industry standard data modellike (FSLDM)

• Collaborate with data engineers, data scientists, and other stakeholders to understand requirements and translate them into technical specifications and solutions
  It will be good to have experience in working with No SQL as well as virtualized Database Environment

• Implement data transformations, aggregations, and computations using Spark RDDs, DataFrames, and Datasets, and integrate them with Elasticsearch
  Develop and maintain scalable and fault-tolerant Spark applications, adhering to industry best practices and coding standards
  Troubleshoot and resolve issues related to data processing, performance, and data quality in the Spark-Elasticsearch integration
  Monitor and analyze job performance metrics, identify bottlenecks, and propose optimizations in both Spark and Elasticsearch components

• Prior experience in developing banking application using ETL, Hadoop is mandatory. In depth knowledge of technology stack at global banks is mandatory.

• Flexibility to stretch and take challenges

• Communication & Interpersonal skillsAttitude to learn and execute

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Key Requirements:

·       Strong experience in developing Hadoop/Spark.
·       Strong experience in data lakes (integration of different data sources into the data lake)
·       SQL Stored Procedures/Queries/Functions
·       Unix Scripting
·       Data Architecture (Hadoop)
·       Solid understanding data modelling, indexing strategies, and query optimization
·       Experience with distributed computing, parallel processing, and working with large datasets
·       Familiarity with big data technologies such as Hadoop, Hive, and HDFS
·       Job Scheduling in Control-M
·       Strong problem-solving and analytical skills with the ability to debug and resolve complex issues
·       Familiarity with version control systems (e.g., Git) and collaborative development workflows
·       Excellent communication and teamwork skills with the ability to work effectively in cross-functional teams