Data Architect

Amiga Informatics

$90K — $130K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in computer science or a related field.
  • 10+ years of experience in high-volume ETL/Data Warehousing projects.
  • Expertise in data architecture and logical/physical database models.
  • Proficient in PostgreSQL and Redshift databases.
  • Familiarity with time series databases is an advantage.
  • Extensive experience in developing and deploying Distributed Data Warehouse solutions.
  • Experienced in high-volume ETL solutions like Informatica or Talend.

Responsibilities

  • Manage and optimize data structures and performance tuning.
  • Oversee data ingestion processes into the databases.
  • Monitor system performance and capacity management.
  • Ensure availability and backup/restore operations of data systems.
  • Execute data performance analysis and troubleshooting as necessary.

Benefits

  • Access to continuous professional development opportunities.
  • Collaborative work environment with a focus on innovation.
  • Flexible work arrangements to support work-life balance.
  • Health, dental, and vision insurance options.
  • 401(k) plan with company match.
Full Job Description
Data Architect

Orlando, FL

Fulltime

Job Description:
• Bachelor's degree in computer science or similar studies.
• 10+ years of experience working in a high volume ETL/Data Warehousing projects.
• Deep knowledge on data architecture, logical and physical database models.
• Experience with PostgreSQL and Redshift.
• Experience with time series databases is welcome but not a must.
• Extensive experience in development and deployment of Distributed Data Warehouse solutions.
• Experience with ETL solutions (e.g., Informatica, Talend) in a complex, high-volume data environment.
• Manage data structures, performance management and tuning, data ingest into the databases, system monitoring, capacity management, availability management, backup / restore.
• Should possess strong data analytical skills.
• Able to prioritize and execute tasks in a high-pressure environment.

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