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Big Data Solutions
Big data work requires a specific skillset -- not just knowing Spark syntax, but understanding partitioning strategies, shuffle costs, and when a simpler tool would actually be the better call. We screen for that judgment.
What We Deliver
Core Capabilities
When your data gets big enough that brute force stops working, you need engineers who think in distributed systems. We place Spark, Kafka, and Flink specialists who process data at scale without overengineering the solution.
Distributed Computing
Engineers who configure and optimize Spark and Hadoop clusters for real production workloads, not toy datasets from tutorials.
Stream Processing
Talent experienced with Kafka Streams, Flink, and Spark Structured Streaming for processing high-volume data in real time, with proper fault tolerance.
Data Lake Architecture
Architects who design lakehouse solutions using Delta Lake, Iceberg, or Hudi with ACID guarantees and query performance that analysts can actually work with.
Performance Tuning
Engineers who diagnose slow jobs, reduce unnecessary shuffle, and pick the right partition strategy for your data shape and access patterns.
Technology Stack
Tools & Technologies
Success Stories
Real-World Use Cases
Ad-Tech Processing
A big data engineer we placed built a bidding data pipeline processing over a million events per second for an ad-tech client that had outgrown their previous architecture.
Genomics Analysis
Talent we placed designed a petabyte-scale genomic data processing system for a biotech company, cutting analysis turnaround from weeks to hours.
Log Analytics
An engineer we placed built centralized log processing spanning thousands of production servers for a client drowning in unstructured operational data.
Ready to Build Your Big Data Solutions Team?
Get matched with pre-vetted big data solutions professionals in as little as 48 hours.
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