Data Engineer | (Scala, Spark, SQL) | Hybrid

Hadoop Eco-System Developer

Designs, develops, and implements Hadoop eco-system based applications to support business requirements.

Follows approved life cycle methodologies, creates design documents, and performs program coding and testing. Resolves technical issues through debugging, research, and investigation.

Required Qualifications:

• Option 1: Bachelor’s degree in Computer Science and 4 years' experience in software engineering or related field.
• Option 2: 6 years’ experience in software engineering or related field.
• Option 3: Master's degree in Computer Science and 2 years' experience in software engineering or related field. 3 years' experience in data engineering, database engineering, business intelligence, or business analytics.

Nice to have soft skills:

• 7+ years of experience with 3+ years of Big data development experience
• Experience in HDFS, Hive, Hive UDF’s, MapReduce, Druid, Spark, Python, Hue, Shell Scripting, Unix.
• Demonstrates expertise in writing complex, highly optimized queries across large data sets
• Retail experience and knowledge of commercial data is a huge plus
• Experience with BI Tool Tableau or Looker is a plus

Main Skills:

• Strong experience in Scala, Spark, SQL, Python, Tableau, Power BI and more.
• Design, develop and build database to power Big Data analytical systems.
• Design pipelines from a wide variety of data sources using Spark, SQL, HQL and other technologies.
• Build robust and scalable applications using SQL, Scala/Python and Spark.
• Create real time data streaming and processing using Kafka and/or Spark streaming.
• Build dashboards using Tableau, Power BI and other reporting tools.