RPLN0220578Sr Informatica ETL developer

We are looking for expertise senior Informatica ETL developer who has hands on Informatica Cloud services
Experience designing ETL methodology for supporting data transformations using Informatica Cloud & Informatica
Power Centre (Must)
Experienced with Informatica Intelligent Cloud Services (Mandatory handson Application and Data integration
services)
Should have strong DB experiences Oracle and SQL e.t.c
Proficient in analyzing business processes requirements and translating them into technical requirements (Must)
Proficient in Data Modeling writing complex SQL queries SQL query tuning (Must)
Hands on experience working on Flat files multiple databases like SQL PostgreSQL Oracle or DynamoDB.
Experience in shell scripting / Python Scripting (Desired)
Familiarity with Agile delivery methods (i.e. Scrum Kanban)(Desired)
Nice to have experience in other cloud technologies (Azure/AWS) Linux and Python

Data Engineer responsibilities:

The Data engineer is responsible for initiating development & delivery of analytic solutions in an agile fashion to the
business to provide insights & improvement to business processes.
Engage directly with customers to design develop and deploy solutions on cloud services.
Perform enhancement testing and troubleshooting of applications based on the business needs.
Continuously identify technical risks and gaps; devise mitigation strategies in anticipation of customer needs.
Write specifications documentation and user guides for customer applications.
The Data engineer uses data and their analytical ability to find and interpret rich data sources; manage large
amounts of data; merge data sources; ensure consistency of datasets; create visualizations to aid in understanding data; build
mathematical models using the data; and present and communicate the data insights/findings and produce and present results
with dashboards

Contribute to the exploration and understanding of new tools and techniques and propose improvements to the data
pipeline. Also Integrate the operations data platform with analytical tools such as Spotfire the Data Scientist workbench the
Data Marketplace etc.
Collaborate with Data Architects Business partners Data engineers and Data Scientists to understand data needs to
drive key decision making throughout the company
Implementing a solid robust extensible data warehousing design that supports key business flows.
Performing all the necessary data transformations to populate data into a warehouse table structure that is optimized
for reporting and analysis; Deploy inclusive data quality checks to ensure high quality of data
Invent and simplify business processes to streamline workflows. Build and improve existing processes to ensure data
integrity and efficient analyse