Hi,

*Please share resume at [email protected] <[email protected]>*


Hope you are doing fine.

Please go through the job description for *DIDV (Data Virtualization and
Integration Engineer/Architect) *for the client based in their *Warren, NJ
OR New York, NY * location for long term project.



*Job Title: DIDV (Data Virtualization and Integration Engineer/Architect)*



*Location: Warren, NJ OR New York, NY*



*Duration: 12 Months +*











*Position: *Data Virtualization and Integration Engineer/Architect



*Responsibilities:*

The architect will be responsible for design development and support of
components of a global data virtualization, integration and delivery
platform::



·         Design, implementation and support of data virtualization and
integration metadata repositories.

·         Design, implementation and support of distributed query
generation and optimization algorithms.

·         Design, implementation and support of virtualization services for
geographically distributed data sources.





*Required Knowledge:*



Educational Background or Professional Experience in the Following Areas:

·         Data Structures: Arrays, Lists, Queues, Heaps, Stacks, Trees,
Graphs.

·         Algorithms: Sorting, Searching, Hashing, Parsing,
divide-and-conquer, dynamic programming, greedy algorithms, graph
algorithms, shortest paths algorithms.

·         Data Models: Conceptual, Logical, and Physical. Metadata Modeling.

·         Relational Data Models. Components, Relation Types, Normal Forms
and Normalization Procedures.

·         Relational Data Models Design.

·         Data Modeling Patterns: Super type-subtype, Data Versioning, Star
Schemas, Dimensional Modeling. De-Normalization Procedures.

·         SQL Concepts.

·         SQL Statements: Parsing, Transformation, Optimization and
Execution.

·         Access Paths, Join Types and Join Algorithms, Aggregation
Algorithms.

·         Aggregation Functions. Analytic Functions.

·         Data Processing Performance Vehicles: Indexes and Indexing
Strategies Materialized Views, Clusters, Caching, Partitioning, and
Parallel Processing.

·         Transactions: Definition and Properties: Atomicity, Consistency,
Isolation, and Durability. Isolation Levels. Locking Strategies.

·         Distributed Databases. Distributed Processing and Distributed
Transactions. Two Phase Commit. Data Replication Architectures.





*Desirable Knowledge and Experience:*



Knowledge or experience with any of the following topics would be an
advantage.



·         Database Architectures: Transactional Data Stores, Operational
Data Stores, Data Warehouses, Data Marts.

·         Query optimization strategies, access paths, execution plans.

·         Extensible hashing, B+Trees, R+Trees.

·         Cache Management Strategies.

·         Security and Data Access Management in Enterprise DB Servers.

·         Large Data Volumes Processing Architectures. Hardware
Architectures, Parallel Processing Architectures, Data Distribution
Strategies, Partitions, and Clusters.

·         Parallel processing: Pipelined and Partitioned Parallelism.

·         Column Oriented Databases.

·         Query optimization strategies, access paths, execution plans.

·         Transactions: Pessimistic and Optimistic Concurrency Control. Two
Phase Locking; Deadlocks Management.

·         No SQL architectures.

·         MapReduce Architectures.





Thanks and Regards,

Arvind Nagar

Sr.IT Recruiter | Dynamic Software services, Inc

*[email protected]* <[email protected]>* | 415-259-5427: G-Talk: *
*[email protected]* <[email protected]>*  YIM:
arvindnagar951*

766 Sutter Street -13.San Francisco, CA- 94109|

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