Sr. Data Engineer ( big data

We have following urgent role with our DIRECT client

• Development experience with Java, Scala, Flume, Python
• Development background with Spark or Map Reduce/YARN is a must have
• This candidate is expected to have significant application development experience in the past either with Java or Python. We are looking for someone who was a Software Engineer in the past and turned into a Data Engineer and build end to end data pipelines from ground up
• Knowledge/experience on Teradata Physical Design and Implementation,
  Teradata SQL Performance Optimization
• Advanced SQL (preferably Teradata)
• Experience working with large data sets, experience working with distributed computing (
  Map Reduce, Hadoop, Hive, Pig, Apache Spark, etc.)
• Strong Hadoop scripting skills to process petabytes of data
• Experience in Unix/Linux shell scripting or similar programming/scripting knowledge
• Experience in ETL/ processes
• Real time data ingestion (Kafka)

• Experience with Teradata Tools and Utilities (Fast Load, Multi Load, BTEQ, Fast Export)
• Cassandra
• Automic scheduler
• R/R studio, SAS experience a plus
• Presto
• Hbase
• Tableau or similar reporting/dash boarding tool
• Modeling and Data Science background
• Retail industry background

BS degree in specific technical fields like computer science, math, statistics preferred

• Very Strong engineering skills. Should have an analytical approach and have good programming skills.
• Provide business insights, while leveraging internal tools and systems, databases and industry data
• Minimum of 5+ years’ experience. Experience in retail business will be a plus.
• Excellent written and verbal communication skills for varied audiences on engineering subject matter
• Ability to document requirements, data lineage, subject matter in both business and technical terminology.
• Guide and learn from other team members.
• Demonstrated ability to transform business requirements to code, specific analytical reports and tools
• This role will involve coding, analytical modeling, root cause analysis, investigation, debugging, testing and collaboration with the business partners, product managers other engineering team.