Data Engineer with Talend
Posted: 11/04/2024
Job Number: z5G7h3l6a1kMvyS65NP3c7sZpRonib88dZANmnJMP7Q=
Pay Rate: 60-70 Hourly USD
Job Description
Job Title:- Data Engineer with Talend
Location:- Richmond, VA(Onsite)
Job Type:- Contract
Position Overview:
Strong understanding of Data warehousing (Dimensional Modeling, ETL etc.) and RDBMS concepts
- Minimum 5 years working experience with Talend ETL tool
- Minimum 5 years working experience in SQL, Stored Procedures and Table Design
- Minimum 5 years working experience in SQL Query optimization and ETL Data loading Performance
- Minimum 2 years working experience in Snowflake Cloud Data warehouse
- Experience as a Data Engineer in Hadoop Platforms on components like HIVE, KAFKA, NiFi, Spark etc is a big plus.
- Minimum 2 years working experience in shell scripting
- Experience in real time streaming technologies is preferred
- Experience deploying machine learning models and automating processes in production is a plus
- Experience with cloud technologies(AWS, Azure, GCP) is big plus
Responsibilities:
As a core member of team of Data Engineers/ETL Developers, responsibilities include but not limited to
- Design, Develop and maintain secure, consistent and reliable ETL solutions supporting critical business processes across the various Business Units.
- Ensure data solutions are compliant with enterprise security standards
- Work in complex multi-platform environments on multiple project assignments.
- Develop and perform tests and validate data flows and prepare ETL processes to meet complex business requirements, including designing and implementing of complex end-to-end solutions using BI platforms.
- Coordinate with analysts and developers to ensure jobs designed and developed meet minimum support standards and best practices before migration into the production environment.
- Partner with various infrastructure teams, application teams, and architects to generate process designs and complex transformations to various data elements to provide the Business with insights into their business processes.
- Uses strategies such as Indexing and partitioning to fine tune the data warehouse and big data environments to improve the query response time and scalability.
- Define and capture metadata and rules associated with ETL processes.
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