Recruit experienced big data engineers who build distributed data systems capable of ingesting, processing, and serving massive volumes at speed. From Hadoop clusters to real-time streaming, they turn data complexity into competitive advantage.
The era of big data demands engineers who understand distributed computing at a deep level, from the nuances of Spark executor tuning to the trade-offs between exactly-once and at-least-once stream processing. Our big data engineers have built production pipelines on Hadoop, Spark, Flink, and Kafka that process terabytes to petabytes daily across industries like telecom, e-commerce, and financial services. They design architectures that balance throughput, latency, and cost to meet your specific SLAs.
Each engineer in our talent pool brings expertise in data lakehouse architectures, combining the flexibility of data lakes with the governance of data warehouses. They implement medallion architectures with Delta Lake or Apache Iceberg, build real-time analytics layers with Flink and ClickHouse, and orchestrate complex workflows with Airflow or Dagster. By embedding data quality checks, schema evolution, and lineage tracking into every pipeline, they ensure your data is not just big but trustworthy and actionable.
Optimizes Spark jobs through partition tuning, broadcast joins, and memory management for maximum throughput on YARN or K8s.
Builds real-time pipelines with Apache Flink and Kafka Streams that deliver sub-second processing guarantees at scale.
Architects lakehouse patterns using Delta Lake, Apache Iceberg, or Hudi with ACID transactions and time travel.
Designs reliable, observable DAGs with Apache Airflow or Dagster that handle dependencies, retries, and SLA monitoring.
Manages HDFS, YARN, Hive, and HBase clusters with capacity planning, rack awareness, and high-availability configuration.
Implements Great Expectations, schema registries, and column-level lineage to maintain trust and compliance across datasets.
Choose the engagement model that best fits your project needs, timeline, and budget.
A full-time big data engineer embedded in your data team for ongoing pipeline development and platform operations.
A project team assembled to design and deploy a lakehouse or streaming platform from architecture through production launch.
Engineers engaged to migrate legacy ETL jobs to modern Spark, Flink, or dbt-based pipelines with zero data loss.
A specialist who profiles your data workloads, identifies bottlenecks, and delivers a tuning plan with measurable improvements.
Optimized Spark and Flink pipelines process terabytes per hour, keeping up with the fastest-growing data volumes.
Streaming architectures deliver analytics within seconds of event arrival, enabling time-critical business decisions.
Right-sized clusters, spot instances, and adaptive query execution reduce compute costs without sacrificing performance.
Automated quality gates and lineage tracking ensure downstream consumers always work with accurate, complete data.
Iceberg and Delta Lake support schema evolution and time travel, letting pipelines adapt without breaking consumers.
Decoupled ingestion, processing, and serving layers scale independently to match growth in data volume and user count.
Four simple steps from requirement to delivery.
Tell us about the role, skills, experience level, and engagement duration you need.
Our team identifies pre-vetted professionals from our talent pool who fit your exact needs.
You interview candidates and select the best fit. We handle onboarding logistics and setup.
Your augmented team member starts delivering. Scale up or adjust as your needs evolve.
Our engineers understand the internals of Spark, Flink, and Kafka, not just the APIs, enabling them to debug the hardest issues.
They have built pipelines that process petabytes daily, so they know what works at scale and what breaks under pressure.
Our team has implemented Delta Lake and Iceberg lakehouses for multiple enterprises, establishing best practices for each.
Engineers cover ingestion, transformation, orchestration, and serving, so you get end-to-end delivery from a single team.
Get pre-vetted professionals onboarded within 48 hours. Start accelerating your projects today.
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