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Epicareer might not working properly because your browser javascript is turned off.

What is JavaScript?

JavaScript is like the magic behind making websites interactive. Basically, it makes Epicareer more enjoyable and engaging.
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Find tutorial for your browser below :
  1. Make sure the webpage is open.
  2. In the Safari app on your Mac, choose Safari > Preferences, then click Security.
  3. Make sure the Enable JavaScript checkbox is selected.
  4. Click Websites.
  5. On the left, click Content Blockers.
  6. Make sure Off is chosen in the pop-up menu next to the website.
  7. On the left, click Pop-up Windows.
  8. Make sure Allow is chosen in the pop-up menu next to the website.
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  1. Open Chrome on your computer.
  2. Click. then Settings.
  3. Click Privacy and Security.
  4. Click Site settings.
  5. Click JavaScript.
  6. Select Sites can use Javascript.
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  1. If you're running Windows OS, in the Firefox window, click Tools > Options.
  2. Tip: If you're running Mac OS, click the Firefox drop-down list > Preferences.
  3. On the Content tab, click the Enable JavaScript check box.
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  1. Click the "Settings and more" icon at the top right of the Edge browser window.
  2. Click Settings.
  3. From the Settings menu, click Cookies and site permissions.
  4. Scroll down and click on JavaScript.
  5. In the JavaScript window, toggle the slider to "on" or "allowed."
  6. Close the Settings tab.
  7. Refresh the page.
Visit Site here
  1. Go to Settings.
  2. Click Advanced in the left sidebar, and click Privacy & security.
  3. Under Privacy and security, click Site settings.
  4. Click JavaScript.
  5. At the top, turn on or off Allowed (recommended).
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Jobs or company...
V

Sr. Data Engineer

  • Full Time, onsite
  • VASG (Vista Applied Solutions Group)
  • Hybrid, United States of America
Salary undisclosed
Checking job availability...
Original
Simplified

Looking for someone to work on our W2

Role: Sr. Data Engineer

Location: Washington, DC

Duration: Long Term

Hybrid Onsite: 4 days onsite per week from Day 1

Minimum year of experience: 10+ Years

Overview:

A professional in data modeling and synthesis is responsible for designing, implementing, and maintaining data structures that support organizational data needs.
This role encompasses various tasks, including connecting multiple data sources, creating data synthesis flows, and working with Big Data(Databricks and PySpark), AI, and Gen AI technologies to drive data-driven insights and automation.

Key Responsibilities:

  • Data Modeling: Design and implement conceptual, logical, and physical data models to support business requirements.
  • Data Synthesis: Develop processes to synthesize data from various sources, ensuring that it is clean, accurate, and ready for analysis.
  • Connecting Data Sources: Integrate multiple data sources into a unified system, facilitating seamless data flow and accessibility.
  • Data Flow Creation: Create and manage workflows that define how data moves through systems, ensuring efficient processing and storage.
  • Big Data Experience: Utilize big data technologies (like Databricks, and PySpark) to handle large volumes of structured and unstructured data.
  • Databricks & PySpark Implementation: Build scalable ETL pipelines using Databricks and PySpark, optimizing data transformations and processing for analytics.
  • Collaboration: Work closely with data architects, analysts, and IT teams to align data strategies with business objectives.
  • AI & Gen AI Exposure:
  • Leverage AI/ML models to enhance data processing, transformation, and analysis.
  • Work with Gen AI frameworks (like OpenAI, Hugging Face, or LangChain) for data-driven automation and insights generation.
  • Implement AI-powered data pipelines to optimize data quality, enrichment, and predictive analytics.

Required Skills

  • Technical Proficiency: Strong knowledge of SQL, Databricks, and PySpark, along with experience in data modeling tools (e.g., Microsoft Visio).
  • Data Architecture Understanding: Familiarity with relational databases, big data frameworks and ETL processes.
  • Analytical Skills: Ability to analyze complex datasets and derive actionable insights.
  • Communication Skills: Excellent verbal and written communication skills to convey technical concepts to non-technical stakeholders.
  • Problem-Solving Abilities: Strong troubleshooting skills to identify and resolve data-related issues efficiently.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
Report this job

Looking for someone to work on our W2

Role: Sr. Data Engineer

Location: Washington, DC

Duration: Long Term

Hybrid Onsite: 4 days onsite per week from Day 1

Minimum year of experience: 10+ Years

Overview:

A professional in data modeling and synthesis is responsible for designing, implementing, and maintaining data structures that support organizational data needs.
This role encompasses various tasks, including connecting multiple data sources, creating data synthesis flows, and working with Big Data(Databricks and PySpark), AI, and Gen AI technologies to drive data-driven insights and automation.

Key Responsibilities:

  • Data Modeling: Design and implement conceptual, logical, and physical data models to support business requirements.
  • Data Synthesis: Develop processes to synthesize data from various sources, ensuring that it is clean, accurate, and ready for analysis.
  • Connecting Data Sources: Integrate multiple data sources into a unified system, facilitating seamless data flow and accessibility.
  • Data Flow Creation: Create and manage workflows that define how data moves through systems, ensuring efficient processing and storage.
  • Big Data Experience: Utilize big data technologies (like Databricks, and PySpark) to handle large volumes of structured and unstructured data.
  • Databricks & PySpark Implementation: Build scalable ETL pipelines using Databricks and PySpark, optimizing data transformations and processing for analytics.
  • Collaboration: Work closely with data architects, analysts, and IT teams to align data strategies with business objectives.
  • AI & Gen AI Exposure:
  • Leverage AI/ML models to enhance data processing, transformation, and analysis.
  • Work with Gen AI frameworks (like OpenAI, Hugging Face, or LangChain) for data-driven automation and insights generation.
  • Implement AI-powered data pipelines to optimize data quality, enrichment, and predictive analytics.

Required Skills

  • Technical Proficiency: Strong knowledge of SQL, Databricks, and PySpark, along with experience in data modeling tools (e.g., Microsoft Visio).
  • Data Architecture Understanding: Familiarity with relational databases, big data frameworks and ETL processes.
  • Analytical Skills: Ability to analyze complex datasets and derive actionable insights.
  • Communication Skills: Excellent verbal and written communication skills to convey technical concepts to non-technical stakeholders.
  • Problem-Solving Abilities: Strong troubleshooting skills to identify and resolve data-related issues efficiently.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
Report this job