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Senior Data Engineer
Senior Data Engineer
Genesys's logo

Senior Data Engineer

Manojkumar Ganesh's profile picture
Posted by Manojkumar Ganesh
4 - 10 yrs
₹10L - ₹40L / yr
Chennai, Hyderabad
Skills
ETL
Datawarehousing
Business Intelligence (BI)
Big Data
Spark
Hadoop
Data engineering
PySpark
Amazon S3
Amazon EMR
Kinesis

Join our team

 

We're looking for an experienced and passionate Data Engineer to join our team. Our vision is to empower Genesys to leverage data to drive better customer and business outcomes. Our batch and streaming solutions turn vast amounts of data into useful insights. If you’re interested in working with the latest big data technologies, using industry leading BI analytics and visualization tools, and bringing the power of data to our customers’ fingertips then this position is for you!

 

Our ideal candidate thrives in a fast-paced environment, enjoys the challenge of highly complex business contexts (that are typically being defined in real-time), and, above all, is a passionate about data and analytics.

 

 

What you'll get to do

 

  • Work in an agile development environment, constantly shipping and iterating.
  • Develop high quality batch and streaming big data pipelines.
  • Interface with our Data Consumers, gathering requirements, and delivering complete data solutions.
  • Own the design, development, and maintenance of datasets that drive key business decisions.
  • Support, monitor and maintain the data models
  • Adopt and define the standards and best practices in data engineering including data integrity, performance optimization, validation, reliability, and documentation.
  • Keep up-to-date with advances in big data technologies and run pilots to design the data architecture to scale with the increased data volume using cloud services.
  • Triage many possible courses of action in a high-ambiguity environment, making use of both quantitative analysis and business judgment.

 

Your experience should include

 

  • Bachelor’s degree in CS or related technical field.
  • 5+ years of experience in data modelling, data development, and data warehousing.
  • Experience working with Big Data technologies (Hadoop, Hive, Spark, Kafka, Kinesis).
  • Experience with large scale data processing systems for both batch and streaming technologies (Hadoop, Spark, Kinesis, Flink).
  • Experience in programming using Python, Java or Scala.
  • Experience with data orchestration tools (Airflow, Oozie, Step Functions).
  • Solid understanding of database technologies including NoSQL and SQL.
  • Strong in SQL queries (experience with Snowflake Cloud Datawarehouse is a plus)
  • Work experience in Talend is a plus
  • Track record of delivering reliable data pipelines with solid test infrastructure, CICD, data quality checks, monitoring, and alerting.
  • Strong organizational and multitasking skills with ability to balance competing priorities.
  • Excellent communication (verbal and written) and interpersonal skills and an ability to effectively communicate with both business and technical teams.
  • An ability to work in a fast-paced environment where continuous innovation is occurring, and ambiguity is the norm.

 

Good to have

  • Experience with AWS big data technologies - S3, EMR, Kinesis, Redshift, Glue
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Subodh Popalwar

Software Engineer, Memorres
For 2 years, I had trouble finding a company with good work culture and a role that will help me grow in my career. Soon after I started using Cutshort, I had access to information about the work culture, compensation and what each company was clearly offering.
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About Genesys

Founded :
1990
Type :
Product
Size :
5000+
Stage :
Profitable
About
Genesys is a leader for omnichannel customer experience & contact center solutions, trusted by 10,000+ companies in over 100 countries.
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Subodh Popalwar

Software Engineer, Memorres
For 2 years, I had trouble finding a company with good work culture and a role that will help me grow in my career. Soon after I started using Cutshort, I had access to information about the work culture, compensation and what each company was clearly offering.
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