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Data Anlayst
Ref No.: 18-02547
Location: Totowa, New Jersey

SQL Development (25%):
  1. Proficient in writing and optimizing SQL queries.
  2. Maintenance of complex functions, scripts, dynamic queries, stored procedures and triggers to support application development.
  3. Sound knowledge of RDBMS concepts.
  4. Provide experience with SQL Server, PostgreSQL and Amazon Redshift.

ETL and Reporting (25%):
  1. Work with business users to establish reporting and analytics requirements.
  2. Translate business requirements into ETL and report specifications.
  3. Develop and implement ETL processes, reports and queries in support of business analytics, using SSIS, Pentaho PDI, SSRS, Tableau, JasperSoft Embedded BI, or other 3rdparty reporting solutions.
  4. Compile ad-hoc data and report requests.
  5. Ensure effective communication of user requirements.
  6. Participates in the evaluation of new business intelligence technologies such as data modeling, ETL, appliances, reporting tools and portal solutions. Many or all of these may be non-Microsoft technologies.

Database Management (25%):
  1. Perform and maintain database backups.
  2. Plan and deploy patches or service packs for SQL Server.
  3. Manage server hardening and security research and implementation.
  4. Independently analyze, solve, and correct issues in real time, providing problem resolution end-to-end.
  5. Configure and maintain database servers and processes, including monitoring of system health and performance, to ensure high levels of performance, availability, and security.
  6. Provide hands-on skills with SQL Server Clustering.
  7. Monitor and manage Amazon RDS PostgreSQL and Redshift cloud environments.
  8. Evaluate, design and implement hybrid on-premise/cloud database environments.

Data Warehouse (20%):
  1. Design, document, maintain and publish data flow diagrams depicting source to target mappings supporting a tiered data architecture comprised of source systems, an operational data store (ODS), data warehouse (DW) and data marts (DM).
  2. Bring expert understanding of data warehouse concepts such as star schemas, snow flake schemas, operational data stores, data warehouses and data marts.
  3. Work collaboratively with key business users to understand their information needs and provide high quality, high performing and intuitive data solutions.
  4. Be self-motivated, able to work independently and collaboratively with peers to identify, understand and analyze complex data in a variety of source systems.

Account Management (5%)