Data Engineering Services
Data, engineered for impact
Overwhelmed by scattered data and slow insights? We build custom data engineering solutions designed around your workflows and business goals, so you can make smarter decisions, faster.
Trusted by 300+ companies worldwide, including industry leaders like:
Gain clarity, speed and control in your data operations
Big data is messy. Integrating sources, ensuring quality, enabling real-time decisions – it can all feel like a maze.
Without the right partner, you risk mounting costs, scattered tools, and data that doesn’t deliver.
At STX Next, we cut through the noise. Our end-to-end data engineering services bring structure, performance, and clarity to your entire data ecosystem.
Tell us about your data engineering needs
Our experts can join your team in under two weeks and start delivering secure, scalable solutions.
Unified Data Platforms
Break down data silos. We design scalable cloud-native platforms with real-time streaming and pipelines built for performance and flexibility. Our automated QA ensures clean, consistent data for all your analytics and AI use cases.
AI-Powered Analytics
Go beyond dashboards. We combine analytics and AI to give you insights you can act on. From workflow optimization to user behavior predictions, our explainable models help your team make confident, real-time decisions.
Real-Time Event Handling
Mission-critical decisions need instant data. We deliver high-speed streaming and anomaly detection to help you monitor operations, prevent fraud, and respond fast. Perfect for IoT, fintech, and logistics.
Some of the data engineering
projects we've delivered:
Transforming brand assurance with AI
Wunderman Thompson, a global marketing communications agency, aimed to create an AI-based platform for brand assurance. Together with STX Next, they successfully optimized their daily operations through the deployment of an advanced ML technology, enhancing their workflow and efficiency.
Advertisement & Marketing
Market research analysis platform
Our market research analysis platform is a tailored solution built for the automotive industry, specifically for one of the globally known, largest automotive manufacturers.
automotive
Data Engineering Solutions built for your Industry
At STX Next, we don’t believe in one-size-fits-all solutions – instead, we partner with you to create data systems that align with your business reality and drive measurable results.
Finance
Financial services thrive on real-time, secure data. We help fintechs and institutions handle complex pipelines and deliver insights fast.
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eCommerce
Retailers need insights that are fast, actionable, and reliable. We build systems that power smarter product, inventory, and customer decisions.
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Healthcare
Data in healthcare must be secure, accurate, and interoperable. Our solutions help healthcare companies unlock patient insights while staying compliant.
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Manufacturing
Operations move fast. We help optimize production, reduce downtime, and make data a core driver of your efficiency.
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Education
EdTech relies on data to enhance learning outcomes and product engagement. We help teams build platforms that scale and adapt.
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Marketing
The right data pipeline can turn campaign chaos into insight-driven performance. We support marketing teams in building scalable systems for attribution, targeting, and optimization.
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Finance
Financial services thrive on real-time, secure data. We help fintechs and institutions handle complex pipelines and deliver insights fast.
Real-time fraud detection
Leverage streaming data pipelines to detect suspicious activity as it happens, minimizing losses and protecting users.
Customer segmentation and scoring
Build unified data models that support precise risk assessments and enable hyper-personalized financial products.
Regulatory reporting
Automate compliance workflows with accurate, up-to-date data pipelines aligned with standards like PSD2, AML, or SEC guidelines.
eCommerce
Retailers need insights that are fast, actionable, and reliable. We build systems that power smarter product, inventory, and customer decisions.
Dynamic inventory forecasting
Use predictive data models to anticipate demand shifts and maintain optimal stock levels.
Customer behavior analytics
Merge data from web, mobile, and CRM systems to better understand customer habits and optimize conversion funnels.
Pricing optimization
Implement real-time data feeds to monitor competitor prices and adjust yours dynamically to boost revenue.
Healthcare
Data in healthcare must be secure, accurate, and interoperable. Our solutions help healthcare companies unlock patient insights while staying compliant.
Medical data integration
Consolidate fragmented data from EMRs, labs, and third-party platforms into a single source of truth for better patient care.
Predictive health analytics
Enable early intervention with ML-powered models that detect patient deterioration risks in real-time.
Compliance-focused data architecture
Ensure HIPAA and GDPR compliance with structured data governance and secure access controls.
Manufacturing
Operations move fast. We help optimize production, reduce downtime, and make data a core driver of your efficiency.
IoT data stream processing
Capture telemetry from industrial sensors and convert it into actionable insights to improve performance and reduce failures.
Supply chain forecasting
Enable accurate demand planning and inventory distribution based on real-time data and historical trends.
Energy and resource optimization
Track usage across facilities and automatically identify inefficiencies that inflate operational costs.
Education
EdTech relies on data to enhance learning outcomes and product engagement. We help teams build platforms that scale and adapt.
Learning progress dashboards
Aggregate student performance data in real time to help educators tailor teaching strategies.
Content recommendation engines
Deliver adaptive learning paths powered by AI and data-driven user profiling.
Operational data centralization
Unify siloed administrative data into a single platform to streamline planning, budgeting, and resource allocation.
Marketing
The right data pipeline can turn campaign chaos into insight-driven performance. We support marketing teams in building scalable systems for attribution, targeting, and optimization.
Cross-channel attribution modeling
Gather touchpoints across campaigns to understand which channels drive ROI and optimize media spend.
Content performance tracking
Build live dashboards powered by real-time metrics to guide campaign tweaks while they’re still running.
Audience targeting systems
Create data models that fuel personalized content delivery and campaign segmentation.
How we work
At STX Next, we combine Agile flexibility with solid engineering principles, ensuring transparency and collaboration throughout the process.
Discovery Workshops
Interactive conversations aimed at carving out clear objectives. We actively involve you to pinpoint tech needs, challenge assumptions, and pick the right solutions.
Development & Prototyping
Focusing on robust design for scalability and security, we often build technical prototypes to test complex components early on.
Incremental & Iterative Development with Sprints
Our Scrum-led teams practice incremental development focused on delivering real business value while adhering to quality standards.
Continuous Integration
& Delivery
Automated pipelines ensure consistent builds, thorough testing, and reliable deployment, boosting efficiency and lowering integration risks.
Proactive Quality Assurance
QA isn’t an afterthought; we integrate it from the get-go, covering performance tests, security checks, and compliance with best practices.
Smooth Deployment
& Handover
Transition seamlessly to your preferred platform with comprehensive documentation for ongoing success.
Tech expertise
We’re not just about listing tech names; we bring deep skills to choose and use the right tools:
Snowflake, Redshift, BigQuery, Databricks, Kafka, Airflow, PostgreSQL, TimescaleDB
Apache Kafka, Flink, Kinesis, OpenTelemetry, Apache Beam
Great Expectations, Monte Carlo, Tableau, Superset, Datafold, Soda SQL
AWS, GCP, Azure, Kubernetes, Terraform, dbt Cloud, Looker, Prometheus, Grafana
TensorFlow, PyTorch, scikit-learn, pandas, NumPy, Spark, Airflow, ML Ops platforms
REST, GraphQL, gRPC, RabbitMQ, Kafka
Jenkins, GitLab CI, GitHub Actions, Prometheus, Grafana, ELK Stack, Cypress, Selenium, Pytest, SonarQube
Scrum, Kanban, Extreme Programming (XP), custom approach (e.g., hybrid), DevOps, Test-Driven Development (TDD), Behavior-Driven Development (BDD), Product Management, Project management, Waterfall, Prince2 Agile
Why choose STX Next?
When complexity demands specialists, STX Next stands out among leading web development companies for your data engineering solutions:
Engineers, Not Just Developers
Our team of over 500 specialized engineers evolved from Python pioneers to AI & Data leaders. We solve the hard technical problems generalists shy away from.
Decades of Experience
Our 20+ years of experience and focus on architecture, testing, and security best practices significantly reduce the risk of project failure, technical debt, and costly mistakes.
Specialized Expertise
Need complex AI integration, massive data handling, or intricate backend logic within your web app? That's our sweet spot. We bring niche skills you can't easily hire or find in generalist firms.
Reliable Processes
Our mature, battle-tested processes ensure transparency and minimize surprises, delivering complex projects more reliably than less experienced teams.
Strategic Technical Partnership
We provide more than code; we offer proactive technical guidance, challenge assumptions constructively, and make sure the solution aligns with your long-term business goals.
Proven Problem Solvers
A track record of successfully untangling complex legacy systems, architecting for massive scale, and delivering innovative features others deemed impossible.
Proven Problem Solvers
A track record of successfully untangling complex legacy systems, architecting for massive scale, and delivering innovative features others deemed impossible.
You earn the trust of your team through the miles that you run together. Over the years, we ran a number of marathons together with STX […] working and sweating side by side. That creates a strong sense of team – not only within STX, but also in the cooperation between Decernis and STX. I really don’t have doubts that if I need something […] they’re there to work with me.
You earn the trust of your team through the miles that you run together. Over the years, we ran a number of marathons together with STX […] working and sweating side by side. That creates a strong sense of team – not only within STX, but also in the cooperation between Decernis and STX. I really don’t have doubts that if I need something […] they’re there to work with me.
Don’t just take our word for it:
Meet your data engineering experts
Get ready to meet the talented individuals who make it all happen. Our team isn't just a group of skilled engineers – they're the people who turn your biggest challenges into great solutions.
An experienced data engineering leader focused on building cloud-native platforms that combine performance, cost efficiency, and quality assurance. He supports business and technology leaders in maximizing the impact of their data initiatives through tailored solutions and strong team collaboration.
Let's talk
Schedule a chat with Tomasz and one of our senior engineers to discuss your data engineering needs.
FAQ
What are data engineering services?
Data engineering services involve building the data infrastructure and tools to ingest, clean, process, and serve raw data from diverse sources. These comprehensive services enable data-driven decision making, support data scientists and analysts, and ensure data quality and data governance throughout the entire data lifecycle.
How do you approach a data engineering project?
Our approach begins with a discovery phase to identify data engineering challenges and validate the best technology stack. We then move into iterative development, focusing on building robust data engineering solutions with continuous data quality testing, integration, and proactive communication. This process covers everything from data ingestion to data storage and data migration, ensuring secure and scalable data pipelines.
What tools do you use?
We leverage industry-leading tools like Apache Airflow, dbt, Spark, Kafka, and Snowflake to build scalable data platforms and pipelines. The exact stack depends on your specific data architecture, cloud provider, and the complexity of your structured and unstructured data.
Can you work with our existing tools?
Absolutely. Our data engineering consultants specialize in integrating data from legacy systems and diverse sources, building modular and flexible data systems that complement your current data infrastructure and improve data observability and data governance frameworks.
How much do data engineering services cost?
Costs vary depending on the scope and complexity of your project. Many clients start with a PoC to minimize risk and assess feasibility. Our services range from short-term maintenance services and data migration projects to enterprise-scale big data engineering services and data fabric implementations.
What makes STX Next different?
Our combination of deep technical knowledge in data engineering, clear communication, and extensive industry-specific experience sets us apart. We build robust data foundations that improve data integrity and security, helping businesses transform their data assets into actionable insights and gain a competitive edge through advanced analytics.
What kind of ongoing support do you provide?
We offer continuous data operations support, including performance tuning, data quality testing, and scaling solutions. Whether you need new features, data governance audits, or help managing your data workflows, our team supports your business long-term.
How do you ensure data security and compliance?
We embed best practices for data security, including strict access controls and compliance with GDPR, HIPAA, and other regulations. Our solutions address the challenges of handling sensitive data securely across the entire data lifecycle.
