Empower your business with custom data engineering solutions designed to optimize operations and unlock the full potential of your enterprise data. From scalable pipelines to real-time processing and advanced DataOps, our expertise ensures your data fuels smarter decisions and competitive growth. Our data engineering expertise has earned the trust of renowned enterprises across industries.
Next steps for your data engineering transformation journey
Strategize with Xenoss
Partner with our specialists to define strategic priorities, assess the current data landscape and identify gaps, and prioritize use cases. We help you select core technologies, ensure data and IP security, and align your data strategy with business goals, processes, and key stakeholders — all to create measurable business impacts
Design the blueprint with Xenoss
Work closely with our experts to conduct a comprehensive discovery and assessment phase, defining your use case objectives and setting clear goals. We help you select the right frameworks and technology accelerators for your needs, and collaboratively design architecture patterns, addressing constraints and finalizing recommendations—all to ensure an efficient and scalable data solution
Build with Xenoss
Collaborate with Xenoss to refine or validate your existing architecture, develop a working prototype with expert support, and create a clear roadmap for production. Together, we’ll ensure your solution is built for real-world success
Data engineering suite: Capabilities for complex, scalable systems
Data fabric
We architect data fabrics that unify access to distributed data sources, connecting silos across cloud, on-premise, and edge, with built-in lineage, governance, and schema control.
Data platforms
We build custom platforms to support ingest, storage, and analytics at scale, integrating tools like Kafka, Spark, Delta Lake, or BigQuery to match your data ecosystem.
We engineer batch, micro-batch, and real-time pipelines for ingestion, transformation, and routing, with monitoring, retries, and data quality checks baked in.
Data infrastructure
Xenoss delivers complete data infrastructure solutions that enable efficient data storage and processing, providing scalability, reliability, and security for all of your data operations.
We execute secure, zero-downtime data migrations between platforms, ensuring schema integrity, consistency, and pipeline continuity during upgrades or stack transitions.
Data mining and preparation
Our data mining and preparation services help you cleanse and transform raw datasets into clean, structured, and ready-to-use data to fuel downstream processes and analytics.
Infrastructure cost optimization
We identify redundant pipelines, inefficient queries, and underutilized resources and then re-architect for cost efficiency without sacrificing performance.
We provide data stack integration services to connect your tools, from ingestion to BI, into a seamless, reliable stack using message buses, orchestration frameworks, and custom APIs.
Real-time data solutions
We build stream-first architectures that support low-latency processing, push-based analytics, and live monitoring across high-frequency systems.
Data analytics solutions
Xenoss builds data analytics solutions that help you generate actionable insights, providing visibility into key metrics to inform better business and engineering decisions.
Data visualization & reporting solutions
We develop visualization and reporting tools that turn complex data into understandable visuals, making it easier for you and your stakeholders to interpret and act on key insights.
Enterprise application modernization services
We decouple monoliths, migrate legacy apps to modern data frameworks, and wrap legacy logic in scalable, API-first infrastructure, future-proofing your architecture.
Data strategy
Our data strategy services help engineering leaders design a data roadmap, ensuring your organization gets the most value out of its data assets and is set up for long-term success.
Data engineering consulting
We provide expert consulting on data architecture, helping you design, build, and optimize your data infrastructure for efficiency, reliability, and scalability.
Business intelligence
Xenoss delivers BI solutions that empower data teams to extract actionable insights, enabling data-driven strategies and enhancing decision-making across the organization.
Connect and unify data from multiple systems, formats, and ingestion protocols with schema enforcement and transformation logic.
Low data quality
Automate detection, cleansing, deduplication, and enrichment of fragmented or messy datasets to improve model readiness and reporting accuracy.
Limited scalability of data pipelines
Redesign batch and stream pipelines for performance at scale with partitioning, queuing, and orchestration built for high-throughput workloads.
Inability to process real-time data
Build low-latency data systems using Kafka, Flink, or Spark Structured Streaming, enabling sub-second decisioning and alerting.
Data security vulnerabilities
Implement end-to-end encryption, access controls, backups, and monitoring to secure pipelines and meet compliance requirements like GDPR or SOC 2.
High costs and suboptimal storage solutions
Optimize resource usage with auto-scaling architectures, columnar storage formats, and query-efficient design patterns.
Insufficient pipeline monitoring and debugging
Embed observability into your pipelines with metrics, logs, alerting, and automated error recovery to reduce data downtime.
Data siloing across departments
Facilitate cross-department communication with all-in-one platforms designed by Xenoss engineers.
Data duplication and redundancy
Eliminate duplicate records and noisy joins by enforcing schema standards, matching keys, and integrating deduplication logic directly into pipelines.
Repetitive tasks
Automate routine data engineering workflows, from validation and enrichment to deployment and alerting, using triggers, DAGs, and CI/CD for pipelines.
Challenges with data archiving and retention
Implement intelligent archiving strategies with automated tiering, TTL policies, and storage rules that align with compliance and performance goals.
Lack of transparency in data lineage and governance
Enable full visibility into data flow, ownership, and transformations through metadata tracking, lineage visualization, and governance frameworks (e.g., DataHub, Marquez).
Why Xenoss is trusted to build enterprise-grade data systems
World’s leader in streaming pipelines
We build ultra-low-latency streaming architectures that process petabytes of data in real time, supporting fraud detection, personalization, and operational decisions at scale.
Proven performance at high load
Our systems power millions of daily operations across mission-critical workloads, engineered for throughput, fault tolerance, and global availability.
Proven enterprise track record
We’ve delivered complex, scalable platforms for large-scale enterprises, integrating across cloud, data lakes, legacy tools, and modern MLOps.
Speed of delivery
Utilize Xenoss’s pre-built development accelerators to get your data solutions delivered extremely fast.
Multi-cloud engineering
We design hybrid and multi-cloud architectures optimized for resilience, cost control, and latency, integrating across AWS, Azure, GCP, and on-premise.
Tech agnostic
We adapt to your tech stack and ecosystem, Spark or Flink, Kafka or Pulsar, dbt or Airflow, without pushing any vendor lock-in.
End-to-end solution architecture
Work with experts who bridge the gap between business challenges and technical solutions, ensuring seamless integration from strategy through implementation and beyond.
Business-aligned engineering
Partner with Xenoss team that combines technical expertise with business acumen, delivering solutions that align perfectly with your enterprise objectives and drive measurable ROI.
Data tech stack behind Xenoss’ projects
Empowering enterprises through hyperscalers and technology data toolset
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.
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.
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.
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.
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
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.
Oli Marlow Thomas
Founder and CIO Smartly.io
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.
FAQ
What does a data engineer consultant do?
A data engineering consultant helps organizations design, build, and optimize data infrastructure for effective data-driven decision-making. They provide data engineering consulting services like developing data pipelines, data lakes, and analytics. Consultants from data engineering companies also assist with data strategy and business use case solutioning.
Whether exploring data engineering with AWS, AI strategy, or data engineering in finance, data engineering consulting firms provide tailored solutions, including data engineering as a service. By partnering with data engineering companies or service providers, businesses can leverage expertise to build reliable and future-proof data systems.
What is the difference between a data engineer and a data consultant?
A data engineer focuses on building, developing, and maintaining data infrastructure, such as data pipelines, data lakes, and data warehouses. They ensure that data is collected, stored, and made accessible efficiently for analysis. Data engineering consulting services often involve designing scalable data solutions, managing data quality, and implementing technologies like AWS for data processing.
On the other hand, a data consultant works more strategically, helping companies understand their data needs and advising on how to best leverage their data for decision-making and achieving business objectives. They often work with stakeholders to define data strategies and align technical capabilities with business goals. While data engineers are hands-on with coding and system architecture, data consultants take a more advisory role, which can involve data strategy development, assessing business use cases, and recommending data solutions.
In short, data engineers are builders, focusing on technical implementation, while data consultants are advisors, focusing on strategic alignment and planning.
What does a data engineer do in a company?
A data engineer is responsible for designing, building, and managing the data infrastructure that supports a company’s analytics and business intelligence needs. This includes creating data pipelines that extract, transform, and load (ETL) data from various sources into data warehouses or data lakes, ensuring that the data is reliable, scalable, and available for analysis.
They also work to optimize data flow, improve data quality, and make sure that data systems are efficient and secure. Data engineers often collaborate closely with data scientists, analysts, and other business teams to understand data needs and provide the necessary infrastructure for insights and decision-making. They use technologies such as AWS, Spark, or SQL to create solutions that transform raw data into structured formats that the company can leverage for analytics and reporting.
