Hyderabad, Telangana, India
Information Technology
Full-Time
Jaggaer
Overview
Overview:
JAGGAER is looking for a Senior Data Engineer to join our Data Pipeline team and help build the technologies used to drive our advanced Analytics capabilities. You will be part of a team responsible for the vision and architecture of scalable data pipeline solutions utilizing various data movement and transformation technologies. You will join a strong team of data engineers what will create high-performance, optimized, and robust date pipeline processes to move data from disparate sources from around the globe.
Principal Responsibilities: - Contribute, as part of a team, in designing, testing, and implementing sophisticated data pipeline technologies to extract and transform data from source systems
- Perform data-modeling on target systems to store data and support analytic querying
- Communicate with other development teams to gather and document requirements
- Work in Agile methodology and participate in design and review meetings
- Follow best practices for the software development life-cycle including coding standards, reviews, source management, build and testing
- Collaborate with other engineers in the team to implement best-practices around large scale data processing
- 5+ years of experience as a Data Engineer or in a similar role working with large data sets and ELT/ETL processes
- 7+ years of industry experience in software development
- Knowledge and practical use of a wide variety of RDBMS technologies such as MySQL, Postgres, SQL Server or Oracle
- Use of cloud-based data warehouse technologies including Snowflake, AWS RedShift.
- Strong SQL experience with an emphasis on analytic queries and performance
- Experience with various “NoSQL” technologies such as MongoDB or ElasticSearch
- Familiarity with either native database or external change-data-capture technologies
- Practical use of various data formats such as CSV, XML, JSON, and Parquet
- Use of Data flow and transformation tools such as Apache Nifi or Talend
- Implementation of ELT processes in languages such as Java, Python or NodeJS
- Use of large, shared data stores such as Amazon S3 or Hadoop File System
- Thorough and practical use of various Data Warehouse data schemas (Snowflake, Star)
#LI-AR1
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