SSIS Developer

  Role Description: SSIS Developer (ETL Dev) - In this role, you will design, develop and test ETL scripts in SQL/SSIS, analyze poor performing scripts, Build dimension models and re write/create new and optimized ETL jobs. Workshift / Slot Normal Shift Experience: 4-8 years of Experience Core Skills
 

• 4 + years relational database experience (SQL Server, SSIS, etc.)
  1. 1 + years of big data experience and strive to learn more with the job
• Proven experience consolidating and analyzing data sources
• Excellent written and verbal communication skills with experience in related complex concepts to non-technical users
• Ability to succeed in a dynamic, fast-paced environment, and quickly find alternative solutions to business and data challenges
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Nice To Have
 

• Experience with other ETL tools like Informatica , Datastage etc > ( Munish- This is also optional and nice to have only)
• Experience in developing and maintaining large databases with complex relationships between tables
• Knowledge of Group Benefits, Group Retirement Services, or Individual Insurance products and systems

Responsibilities:

• Efficient in developing and presenting database solutions to key stakeholders and onsite partners
• Participate in the technical design, development, testing and user documentation and processes
• Should be able to reverse engineer SQL/SSIS code units and re write in efficient and optimized manner ( SQL Server, Stored Procedures)
• Very good experience in writing complex SQL queries, Stored Procedures, User Define Functions, Views, indexes and views with performance tuned
• Builds ETL processes for cleansing, staging, migrating data from various sources(Relational, Big data) to data warehouse
• Strong proficiency in MS SQL Server and prior experience in MS SQL Server performance tuning like Query Optimization, Indexing Strategies
• Excellent understanding of indexes, locks, execution plans and file stats
• Experience in Data Modeling, Database design and well versed with SQL Server best practices 
• Experience with hybrid data environments that leverage both distributed and relational database  technologies to support analytics services
• Good knowledge of Big Data querying tools, such as Pig, Hive, and Impala >>>
  1. Knowledge of various ETL techniques and frameworks, such as Flume (Munish- If you are not getting this combination then optional)