Modern Data Infrastructure in Weeks
You Need This If
Legacy systems drain capacity
Cloud costs keep climbing
Pipelines break constantly
High-risk migration looms
Infrastructure That Solves Operational Problems
Legacy system modernization
Informatica jobs, Perl scripts, and custom ETL need to move to modern tools like Airflow and dbt without downtime or data loss. Both systems run in parallel while outputs get validated. Cutover happens only after proving the new system works reliably.
AI-ready data foundations
Stay on top with real-time insights and automated alerts so you can quickly spot performance shifts and prevent any downtime.
Reliable pipeline infrastructure
Stay on top with real-time insights and automated alerts so you can quickly spot performance shifts and prevent any downtime.
Cost-predictable cloud platforms
Stay on top with real-time insights and automated alerts so you can quickly spot performance shifts and prevent any downtime.
What Makes Us Different
Production operations experience
Parallel migration approach
Complete knowledge transfer
Our 8-16 Weeks Process
Current state assessment
Address urgent issues
Sustainable foundations
Transition and handoff
Sharecare: Member-Facing Health Q&A
Let's Map Out What Needs Fixing
Your Questions Answered
What is enterprise data engineering?
Enterprise data engineering builds and maintains the infrastructure that moves, transforms, and stores data across an organization. This includes pipeline development for data movement, warehouse optimization for cost control, legacy system modernization to replace outdated tools, data quality frameworks to ensure consistency, and governance structures to manage access and compliance.
Why does my organization need data engineering services?
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How long does data infrastructure modernization take?
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What is the difference between data engineering and data science?
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How do you ensure zero downtime during legacy system migration?
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Can you integrate with our existing tech stack?
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How do you optimize Snowflake or Databricks costs?
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What industries benefit most from data engineering services?
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How do I choose a data engineering consultant?
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