Aavalar Consulting is a trusted technology staffing partner that helps technology leaders connect with and deploy in-demand, skilled IT, Engineering and Accounting professionals at client sites across the Mid-Atlantic region. Since 1999, Aavalar Consulting has built an award-winning reputation with over one hundred of the most innovative Fortune 500 and mid-market companies to deliver substantial value through a broad set of technology consulting and staffing services that include: Staff Augmentation, Interim Technology Executives, and Search and Recruitment.
Aavalar has immediate opportunities with a highly visible company in Princeton, NJ for an experienced ETL (Informatica) software engineers. Successful candidates will handle end-to-end Data Warehouse, Data Integration and BI solutions by using business cases, objectives and requirements. The technical domain includes all aspects of the solution including data integration, data architecture, information delivery, infrastructure, testing, performance tuning for all aspects of project.
Title: Informatica ETL Developer
Work Location: Princeton, NJ
Work environment: Professional and modern open office atmosphere
To whom does this position report? Team Lead, Data Warehouse
What is the start date of the contract? ASAP
- Strong understanding of ETL tools, primarily Informatica.
- Very Large Database and Data Warehouse implementation experience (20+ TBs)
- Programming knowledge of Unix
- Strong trouble-shooting and problem-solving skills
- Team player with strong oral and interpersonal skills
- Desire to work under aggressive deadlines
- BI Tool Experience, Cognos a plus.
- Strong Data Modeling skills including ERWIN Data Modeling experience.
- Experience with Oracle and/or GreenPlum databases a plus.
- Ability to promote growth and knowledge of other team members
- Project Management skills including project proposals, estimation, planning, gap analysis, risk analysis
- Understanding of the design and development of high-performance parallel Data Architecture systems
- Understanding of segmentation and partitioning in large database implementations and how bulk loaders can be leveraged to load large amounts of data
- Understanding of backup, archive, restore and purge strategies and disaster recovery strategies in very large database environments.
- Experience with the monitoring and fine-tuning of large data warehouse implementations using various DW performance improvement options (virtual and materialized views; additional indexes; segmentation and partitioning of the various fact tables; caching, etc.).
Work Hours and Schedule: Typical professional day
Dress Code: Business Casual
Interview process: Phone interview with team member followed by an in person with the Hiring Manager for qualified candidates
Compensation: Depends on experience. We are considering all levels of experience.