Why This Role Stands Out
You'll have the opportunity to leverage your Informatica IDMC expertise in a hybrid environment, driving impactful data integration solutions within a reputable firm. This role is ideal for experienced ETL developers with a strong background in Oracle, Hadoop, and Agile methodologies who are eager to enhance their skills and contribute to innovative projects. Apply now to explore this exciting career growth prospect!
Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
Charlotte, NC, United States
Posted
22 hours ago
OracleSQLETLAgileHadoop
Job Description
Primary Skill: Informatica IDMC Developer
Secondary: Oracle, Hadoop
Experience: Minimum 10 years
Roles & Responsibilities
- Bachelor s or master s degree in computer science or related field.
- Minimum 2 years experience in IDMC migration projects.
- ETL Process Development: Design, develop, and maintain ETL processes using Informatica PowerCenter or other relevant Informatica tools.
- Experience in Agile Methodology
- Experience with code versioning tools like Bit-Bucket
- SQL Proficiency: Utilize SQL/PLSQL to extract, transform, and load data.
- Exposure to advanced transformations like data transformations, Parsing JSON/XML messages
- Experience in Job scheduling tools Like Autosys
- Experience with HDFS, MapReduce, and Hadoop ecosystems.
- Understanding data storage and data processing techniques in Hadoop
- Data Integration: Integrate data from various sources, ensuring data consistency and quality.
- Data Warehouse Design: Design and maintain data warehouses to support business intelligence activities.
- Performance Optimization: Optimize SQL script/queries for speed and efficiency.
- Troubleshooting: Identify and resolve issues in ETL processes.
- Documentation: Create and maintain technical documentation for ETL processes.
- Testing: Perform unit, integration, and system testing on ETL processes.
- Collaboration: Collaborate with cross-functional teams to ensure successful implementation of ETL processes.
- Data Quality: Ensure data quality by implementing data cleansing and transformation processes.
- Data Modeling: Develop and maintain relational and dimensional data models.
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