Big Data Processing Services

Big data processing platforms excel at large-scale ETL/ELT pipelines, data lake transformations, ML feature engineering, batch analytics, and reporting workloads. They're ideal when you need to process terabytes to petabytes of data, require complex transformations, or need to consolidate data from multiple sources for analytics and ML.

Use open-source Spark when you need maximum flexibility, have existing Spark expertise, or require fine-grained control over infrastructure. Managed platforms like Databricks or EMR are better when you want reduced operational overhead, built-in collaboration features, or faster time-to-value with less infrastructure management.

We detect skew through execution analysis and implement salting strategies, broadcast joins for small tables, and pre-aggregation patterns. We also tune partition strategies, use adaptive query execution, and design split-apply-combine approaches to balance load across executors for predictable performance.

We implement right-sizing strategies, spot/preemptible instance usage, autoscaling policies, and efficient data layouts. We also optimize shuffle operations, use columnar formats with compression, and implement job scheduling during off-peak hours to reduce compute costs by 30–60%.

We implement retry logic, checkpoint strategies, and idempotent processing patterns. Our designs include failure alerting, automated recovery, and runbooks for incident response. We also conduct failure testing and establish SLOs with monitoring to maintain high availability.

We set up comprehensive monitoring including job health, resource utilization, data quality metrics, and SLA tracking. Alerting covers job failures, performance degradation, and capacity issues. Dashboards provide visibility with drill-down capabilities for troubleshooting.

We design idempotent write patterns with partition-based overwrites and transaction-safe writes to lakehouse formats. Jobs support date-range parameters for backfills, and orchestration handles dependencies and retries automatically. This ensures safe reruns without data duplication.

Yes, we offer 24×7 support for mission-critical workloads including incident response, performance trending, capacity planning, and upgrade management. Our support includes proactive optimization recommendations and regular health reviews to maintain platform reliability.