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Data Virtualization Engineer Jobs in Washington (NOW HIRING)

Quadtec Solutions, Inc

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Cybersecurity Threat Hunter (Data Scientist)

Washington, DC · Remote

$160K - $160K/yr

... data virtualization solutions. It will require close partnerships with other internal teams ... programming tools. • Experience applying statistical analysis to large data sets. • Able to ...

Barrow Wise Consulting

Data Architect

MD · On-site

$90K - $130K/yr

Familiarity with the latest trends in data engineering and data management (APIs, data virtualization, * stream data integration, augmented data integration) * Familiarity with SQL Server database ...

Peraton

Senior Storage Engineer

Washington, DC

Responsibilities Position Summary The Senior Storage Engineer is responsible for the design ... virtualization issues. Backup, Recovery & Data Protection * Administer and support enterprise ...

Stem Xpert

Informatica/ETL Architect

Herndon, VA · On-site

Strong hands on Informatica 9.x/9.5/9.6 experience in architecting, engineering, performance ... of MDM, Data Virtualization, Data Services, Proactive Monitoring, Data Exchange, Data ...

Peraton

Senior Storage Engineer

Washington, DC · On-site

Responsibilities Position Summary The Senior Storage Engineer is responsible for the design ... virtualization issues. Backup, Recovery & Data Protection * Administer and support enterprise ...

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Data Virtualization Engineer information

How does a Data Virtualization Engineer typically collaborate with business analysts and data scientists?

Data Virtualization Engineers play a key role in bridging the gap between raw data and actionable insights by working closely with business analysts and data scientists. They design and maintain virtual data layers that allow these teams to access integrated, real-time data from multiple sources without having to manage the underlying complexities. Regular collaboration often includes requirements gathering, troubleshooting data access issues, and optimizing queries to ensure performance and accuracy. This cross-functional teamwork helps ensure that data-driven decisions are based on timely, trustworthy information.

What are the key skills and qualifications needed to thrive as a Data Virtualization Engineer, and why are they important?

To thrive as a Data Virtualization Engineer, you need expertise in data integration, SQL, data modeling, and a solid understanding of database technologies, often supported by a degree in computer science or related fields. Familiarity with data virtualization tools such as Denodo, Cisco Data Virtualization, or IBM Cloud Pak for Data, as well as certifications in these platforms, are commonly required. Strong problem-solving skills, effective communication, and the ability to collaborate across business and IT teams are valuable soft skills. These competencies are essential for building efficient, scalable data solutions that enable organizations to access and manage data seamlessly from diverse sources.

What is a Data Virtualization Engineer?

A Data Virtualization Engineer is an IT professional who specializes in creating and managing data virtualization solutions, which allow organizations to access and integrate data from multiple sources without physically moving or replicating it. They design, implement, and maintain data virtualization platforms, enabling real-time data access for analytics, reporting, and business intelligence. These engineers work closely with data architects, business analysts, and IT teams to ensure seamless data integration and optimal performance. Their work simplifies data management and helps organizations make faster, data-driven decisions.
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Data Virtualization Engineer jobs near you
Data Engineer AWS - US Citizens

Data Engineer AWS - US Citizens

FRACSYS INC

Leesburg, VA

$120K/yr

Full-time

Posted 8 days ago

Job description

Fracsys Inc is hiring a AWS Data Engineer position. The ideal candidate must have at least 8+ years of industry experience. He or she must be responsible for successful technical delivery of Data Warehousing and Business Intelligence projects.  This positions requires US Citizenship due to Clearance requirements.
Responsibilities

  • Data extraction, Data cleaning, Data Loading, Statistical Data Analysis, Exploratory
    Data Analysis, Data Wrangling,
  • Write complex SQL queries and stored procedures to extract, manipulate, and analyze data from
    relational databases
  • Conduct diagnostic, troubleshooting steps and present conclusions to a varied audience
  • comfortable slinging some code to solve a problem
  • Build Data Marts and Data warehouses to facilitate analytical capabilities across the varied sources of data
  • Design and implement data patterns on cloud using cloud Data warehouse and data virtualization tools
  • Evaluate new tools and technologies for target state on cloud
  • Learn and implement new ETL, BI tools and data warehousing technologies
Qualifications

  • Senior Data professional with over 8 years of expertise in Data Engineering, Data Analysis, and Data
    Science.
  • Experience creating Data Marts, Data warehouses on-premise and on cloud for real time and batch processing frameworks
  • Experience building and optimizing big-data data pipelines and data sets including Postgres, AWS Relational Data Service
  • extensive hands-on experience building and optimizing data structures for data analytics, data science and business intelligence
  • Experience building self-service data consumption patterns and knowledge of cloud-based data Lake platforms
  • Experience wrangling data (structured and unstructured), in-depth knowledge of database architecture
  • Experience utilizing or leading implementations leveraging ETL tools (Informatica / Talend), BI Reporting tools such as MicroStrategy, Microsoft Power BI, data modeling tools such as Erwin, Oracle, SQL server, NoSQL, JDBC, UNIX shell scripting, PERL and JAVA, XML/JSON files, SAS , Python, AWS cloud-native technologies, S3, Athena, Redshift
  • Experience in snowflake is an added bonus.
  • Familiarity with the following technologies: Hadoop, Kafka, Airflow, Hive, Presto, Athena, S3, Aurora, EMR, Spark
  • Ability to drive, contribute to, and communicate solutions to technical product challenges
  • Ability to roll-up your sleeves and work in process or resource gaps and fill it in yourself
  • Excellent written and oral communication skills in English
Education

Bachelor’s degree in computer science, Data Analytics, Information Systems, or a related degree or equivalent experience. Master’s degree is preferred.