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Enterprise data pipeline engineering that eliminates data silos and scales to petabyte workloads

Build real-time and batch processing pipelines with distributed architectures, automated data quality validation, and fault-tolerant systems that handle millions of events per second while maintaining sub-second latency.

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Challenges Xenoss eliminates with enterprise data pipeline engineering

 

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Data silos preventing unified analytics and decision-making

Enterprise data is trapped in disconnected systems – CRM, ERP, databases, APIs, and legacy applications. Teams waste weeks manually extracting and correlating data from multiple sources, creating inconsistent reports and delayed insights that hurt business agility.

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Pipeline failures causing critical business process disruptions

Traditional ETL pipelines break when data formats change, APIs go down, or processing volumes spike. A single failure can cascade through dependent systems, causing executive dashboards to go stale and analytics teams to lose trust in data reliability.

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Inability to process real-time data for time-sensitive operations

Batch processing systems create 6-24 hour delays between data generation and availability. Fraud detection, inventory management, and customer personalization require sub-second data processing that traditional pipelines can’t deliver without massive infrastructure investments.

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Data quality issues corrupting downstream analytics and ML models

Dirty data, schema mismatches, and duplicate records flow through pipelines undetected. Poor data quality costs enterprises $12.9M annually while destroying confidence in AI/ML initiatives and leading to incorrect business decisions based on flawed analytics.

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Manual pipeline management that doesn’t scale with data growth

Data engineering teams spend 80% of their time on maintenance instead of innovation. Manual monitoring, error handling, and performance tuning create bottlenecks that prevent organizations from scaling data operations as business requirements evolve.

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Performance bottlenecks under enterprise-scale data volumes

Pipelines designed for gigabytes fail catastrophically when processing terabytes. Memory limitations, network congestion, and processing inefficiencies create hours-long delays, making real-time analytics impossible and batch jobs miss critical SLA windows.

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Lack of data lineage and observability for compliance auditing

Regulatory compliance requires complete data traceability from source to destination. Without proper lineage tracking and audit trails, enterprises face compliance violations, struggle with data governance, and can’t troubleshoot pipeline issues effectively.

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Vendor lock-in limiting flexibility and increasing long-term costs

Proprietary ETL tools create expensive dependencies with licensing costs that scale with data volume. Organizations lose architectural flexibility, face vendor price increases, and struggle to adopt new technologies that could improve performance or reduce costs.

Build enterprise data pipeline infrastructure from scratch or enhance your existing systems

Synthetic data generation pipelines

Real-time streaming data processing engines

Custom Apache Kafka and Apache Pulsar implementations that process millions of events per second with guaranteed message delivery. Build fault-tolerant streaming architectures with exactly-once processing semantics for financial transactions, IoT telemetry, and user behavior analytics.

API-native process automation

Distributed batch processing platforms

Scalable Apache Spark and Hadoop clusters optimized for petabyte-scale data processing. Implement custom partitioning strategies, memory optimization, and dynamic resource allocation to handle enterprise workloads with predictable performance and cost efficiency.

Data quality and availability

Data quality validation and monitoring systems

Automated data profiling, schema validation, and anomaly detection pipelines that catch quality issues before they corrupt downstream analytics. Real-time monitoring dashboards with configurable alerts for data freshness, completeness, and accuracy violations.

Multi-Cloud strategy implementation

Multi-cloud data integration architectures

Unified data pipelines that seamlessly move data across AWS, Azure, GCP, and on-premise systems. Handle format transformations, API rate limiting, and network optimization to create single source of truth from disparate enterprise data sources.

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Custom ETL/ELT orchestration frameworks

Apache Airflow and Prefect-based workflow management with dependency resolution, retry logic, and parallel execution. Build complex data transformation pipelines with automatic scaling, error recovery, and comprehensive lineage tracking for regulatory compliance.

SageMaker Migration & Optimization

High-performance data storage optimization

Columnar storage implementations using Apache Parquet and Delta Lake with intelligent partitioning and compression. Optimize query performance for analytics workloads while minimizing storage costs through lifecycle management and tiered storage strategies.

Patient data integration

Event-driven microservices data architecture

Decoupled pipeline components using message queues, event sourcing, and CQRS patterns. Build resilient systems where individual services can be updated, scaled, or replaced without affecting the entire data processing workflow.

Human-AI collaboration by design

Data pipeline observability and DevOps automation

Comprehensive monitoring, logging, and alerting systems with distributed tracing for end-to-end pipeline visibility. Implement Infrastructure-as-Code, automated testing, and CI/CD pipelines for reliable deployment and maintenance of data infrastructure.

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Best practices for building scalable, reliable, and secure data pipelines

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Tech stack for data pipeline engineering

Trusted by AI & data-driven companies

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  • Moloco logo
  • Sizmek logo
  • Venatus logo
  • DataSeat logo
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  • Lifesight logo
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  • Smartly logo
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  • entravision
  • Triffecta
  • ARTIFACT
  • ViVV

Why Xenoss is trusted to build enterprise-grade data pipeline infrastructure

We solve the complex engineering challenges that prevent enterprises from scaling data operations reliably.

Built data infrastructure that processes trillions of events for Fortune 500 companies

Engineered production pipelines handling petabyte-scale workloads for Adidas, Uber, and HSBC. Our systems process billions of daily transactions with 99.99% uptime, supporting mission-critical business operations that can’t afford data delays or quality issues.

Mastered distributed systems architecture for fault-tolerant data processing

Built custom Kafka clusters, Spark optimizations, and multi-region failover systems that maintain data consistency during outages. Our distributed architectures handle node failures gracefully while preserving exactly-once processing guarantees for financial and regulatory workloads.

Eliminated data silos through unified pipeline architectures

Integrated 50+ data sources including legacy mainframes, cloud APIs, real-time streams, and batch systems into unified platforms. Our integration frameworks break down organizational data barriers while maintaining security, governance, and compliance requirements.

Optimized pipeline performance to handle 10M+ events per second

Developed proprietary optimization techniques for Spark job tuning, Kafka partitioning strategies, and memory management that deliver 10x performance improvements. Our pipelines maintain consistent throughput even during peak traffic spikes and data volume surges.

Automated monitoring that prevents data quality issues from reaching analytics

Built real-time data profiling, schema validation, and anomaly detection systems that catch quality problems before they corrupt downstream processes. Our observability platforms provide complete data lineage tracking and alert systems for proactive issue resolution.

Reduced infrastructure costs by 60% through intelligent resource optimization

Designed auto-scaling systems with spot instance management, intelligent caching layers, and storage lifecycle policies that minimize cloud costs. Our architectures automatically adjust compute resources based on workload patterns, eliminating over-provisioning waste.

Built GDPR, SOX, and HIPAA-compliant data processing systems

Implemented end-to-end encryption, audit logging, and data governance controls that meet regulatory requirements for financial services and healthcare. Our security frameworks include role-based access controls, data masking, and compliance reporting automation.

Infrastructure-as-Code and CI/CD systems that eliminate manual deployment risks

Created automated testing, deployment, and monitoring systems that reduce pipeline maintenance overhead by 80%. Our DevOps practices include blue-green deployments, automated rollbacks, and comprehensive pipeline health monitoring for operational excellence.

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Process petabyte-scale data with 99.99% uptime and sub-second latency.

Custom streaming and batch architectures built to handle 10M+ events per second with fault-tolerant systems.

Pipeline architecture review

Featured projects

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Ben Dzamba

VP of Product, Powerlinks

Before turning to Xenoss, we had a demand-side platform that was costly and not scalable. Having access to a wealth of experience on the Xenoss team related to our domain of real-time bidding, we’ve cut costs and now have a much more efficient, reliable DSP for our customers. I’d gladly recommend Xenoss as a technology partner. I’ve found the team to be very professional and diligent, ensuring that our needs and expectations are met through every step of the development process.

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Alex Belyansky

Director of Engineering, INMAR

It was a great pleasure working with the Xenoss team. The project was complex and challenging - a rich media editor supporting animation, timeline editing, special effects, undo/redo functionality, and other unique features not commonly found. The project was time-boxed for 3 months. It was a ground-up development incorporating niche technologies that required extensive research and prototyping. Not only did the team deliver a fully working MVP on time, but they also exceeded the requirements in several key instances. The architecture was thoroughly designed, and the UX was executed according to the specifications. I'm very grateful for this experience and highly recommend Xenoss.

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Brandon Keenan

CMO, ViVV LABS

We loaded a huge client into the ViVV Labs Platform today—with the incredible support of the Xenoss team. We’ve done this a number of times already, and it’s worked flawlessly every time, but this one was different. It was a key client for our business. If you want to experience what it’s like to pull your walled garden data effortlessly and apply data science to your spend to potentially save 30–40%, partner with Xenoss.

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David Philippson

CEO & Co-Founder, Dataseat

We were looking for an experienced vendor to develop a performance-based media buying solution from scratch. One of the main reasons why we chose Xenoss was their extensive domain knowledge. It allowed us to save time and effort at the initial stages and dive right in product development. The team’s been very professional and responsive to our needs and was able to deliver the MVP under just several months. Later on, they’ve transformed it into a fully featured platform for in-game advertising, which already proved highly scalable and able to manage high load. I’ve been truly happy with their work, high quality standards, and communication.

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Edward Lyon

Head of Product, Smartly

Our business has grown since we started working with Xenoss by an enormous amount and much of that has to do with the software that they’re developing. The most impressive aspect of our collaboration is that the Xenoss team keeps on solving challenges we put in front of them and these are challenges that anecdotally, other businesses have tried solving but are not successful.

Matt Cannon about Xenoss

Matt Cannon

COO, Venatus

We've been a client of Xenoss for a year now and find them an excellent technology partner. Highly skilled and knowledgeable with the ability to rapidly adapt to our needs. We intend to double the size of our current team with them in 2021.

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Oli Marlow Thomas

CEO & Founder, Smartly

At some point in our business journey, we had a frustrating experience with our product, from barely managing its instability to fixing errors on the fly. Xenoss team helped us build a well-balanced tech organization and deliver the MVP within a very short timeline. It let us timely onboard huge clients such as Adidas, Tesco, Uber, and keep up our growth pace. I’m glad we’ve been working with such a highly-productive team. I particularly appreciate their ability to hire extremely fast and to generate great product ideas and improvements.