TalentWerx

TalentWerx

TalentWerx is a staffing and recruiting company that provides fast, accurate, and innovative solutions to help organizations find the right people to join their teams. We aim to solve the existing problems with traditional talent acquisition firms, suc...

Professional Services
11-50
Founded 2018

Description

  • Build, maintain, and optimize systems that collect, store, process, and convert complex data for analytics and reporting.
  • Manage internal and external data collection, normalization, compilation, and standard analysis across diverse platforms and projects.
  • Develop, evaluate, and test scalable data solutions that support organizational goals and data-driven decision-making.
  • Create and implement data protection, quality, delivery, and value practices across data programs.
  • Investigate data quality issues, perform root-cause analysis, resolve errors, and design process improvements and prototypes.
  • Process, clean, and structure unstructured or complex datasets for analysis and insight generation.
  • Integrate new tools, algorithms, and techniques into existing data systems with engineering teams.
  • Design, build, and execute data projects focused on collecting, parsing, managing, analyzing, and visualizing large datasets.
  • Determine software and hardware architecture needs to support performance and scalability.
  • Collaborate with data scientists, analysts, engineers, business owners, and external clients to define needs and deliver insights.

Requirements

  • Active Secret clearance.
  • Bachelor’s degree and 8–10 years of experience.
  • Advanced expertise in designing, building, and maintaining data warehouses, pipelines, and large-scale distributed data systems.
  • Strong proficiency with modern database technologies, ETL/ELT frameworks, and big data tools.
  • Proficiency in Python, SQL, or Scala.
  • Experience with data governance, quality management, metadata management, and security best practices.
  • Experience with cloud data platforms such as AWS, Azure, or GCP, containerization, and modern DevOps practices.
  • Ability to solve complex technical problems and develop innovative, scalable data solutions.
  • Ability to collaborate with cross-functional teams and communicate technical concepts to non-technical audiences.
  • Preferred experience integrating machine learning into production data systems, real-time data processing, streaming technologies, and data visualization tools such as Power BI or Tableau.
  • Preferred certification in cloud platforms, data engineering, or database technologies.
  • Preferred experience supporting government, defense, or contractual data environments.
  • Preferred certifications include Google Cloud Data Engineer, AWS Data Analytics, or Azure Data Engineer Associate.

Interested in this position?

Apply directly on the company website

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