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Data Architect

Job in Ottawa, Franklin County, Kansas, 66067, USA
Listing for: Jobs via Dice
Full Time position
Listed on 2026-02-28
Job specializations:
  • IT/Tech
    Data Engineer, Data Analyst, Data Warehousing, Data Security
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below
Position: Data Architect (34580)

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Myticas LLC, is seeking the following. Apply via Dice today!

  • 8+ years of experience in Data Architecture, Data Engineering, and Analytics, operating across both strategic and hands-on delivery roles.
  • Proven ability to design conceptual, logical, and physical data architectures, including defining As-Is and To-Be states and building executable data roadmaps.
  • Strong hands-on experience designing and building ETL pipelines, data integrations, and data migration solutions across legacy and modern platforms.
  • Advanced Python development for data extraction, transformation, automation, and analytics; strong SQL across multiple database technologies.
  • Solid understanding of Big Data concepts, including data lakes, Hadoop ecosystem fundamentals, and the 4 V's (Volume, Velocity, Variety, Veracity).
  • Experience leading or supporting analytics and BI platform migrations, including lifting and shifting on-prem Tableau environments to the cloud.
  • Hands-on experience with BI and reporting tools such as Tableau (on-prem & cloud), Power BI, and SAP BI / Business Objects.
  • Demonstrated ability to work directly with Finance, BI, Reporting, and business stakeholders, translating business requirements into scalable data solutions.
  • Experience implementing data catalogues, metadata management, data governance, and database/storage strategies aligned with security and best practices.
  • Exceptional communication and stakeholder-facing skills, with a high degree of autonomy, self-direction, and ability to explain complex data concepts to non-technical audiences.
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