Transform Your Data Into Insights With Our Scalable Data Engineering Services
Our nearshore data engineers and scientists transform raw data into valuable business intelligence through scalable pipelines, AI-powered data analytics, and real-time insights.
Trusted by leading brands across industries
“The engineers at Distillery have delivered at level of capability that far exceeded our expectations. They’ve provided us with a number of 10x developers ensuring quality software and enabling our teams to deliver amazing impact for our customers and partners.”
Reimagined Consulting
CEO
Success Stories
Three Years. One DMP.
How a Distillery data SWOT team enabled a global travel company to revolutionize their data management system.
AI at Its Best.
How Distillery optimized a global recommendation system leveraging the latest in AI and LLMs.             Â
Fortifying Transactions
How Distillery enhanced the payment 
processing system for a global eCommerce firm.           Â
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Powerful Data Engineering Services Designed
to Scale with Your Business
Data Engineering & Pipelines
High-performance data pipelines that automate and optimize data flow.
- Scalable ETL/ELT processes for efficient data transformation and data ingestion.
- Real-time and batch data collection from structured and unstructured sources.
- Automated pipeline orchestration to maintain data integrity and efficiency
Cloud Data Architecture
Flexible, cloud-native data solutions built for scale and performance.
- High-availability architectures on AWS, Azure, and Google Cloud.
- Cost-optimized cloud storage and processing using Azure Data Factory and other cloud-native tools.
Data Warehousing & Storage
Fast, scalable, and secure data storage for instant access and insights.
- Enterprise-grade data warehouses designed for advanced analytics and optimized data modeling.
- Optimized query processing for improved accessibility and reporting.
- Secure, long-term data storage with retrieval capabilities.
DataOps & Automation
Automated data workflows that enhance agility, efficiency, and collaboration.
- Fully automated data pipeline orchestration to reduce manual effort.
- Agile DataOps methodologies for real-time monitoring and governance.
- Continuous integration and deployment (CI/CD) for smooth data workflows.
Predictive Analytics & AI
AI-powered insights that drive smarter decisions and business outcomes.
- Custom predictive models for market trends, forecasting, and risk analysis.
- Automated anomaly detection to enhance operational efficiency.
- Scalable AI integration using TensorFlow, PyTorch, and Scikit-learn.
Business Intelligence (BI) & Data Visualization
Interactive dashboards and reports that turn raw data into actionable insights.
- Real-time data ingestion into data analytics dashboards using Power BI, Tableau, and Looker.
- Custom BI solutions for tracking key business metrics.
- Self-service analytics for data-driven decision-making across teams.
Data Governance & Compliance
Enterprise-grade security and compliance to protect sensitive data.
- End-to-end encryption, access controls, and data privacy frameworks.
- Regulatory compliance with GDPR, HIPAA, SOC 2, and other standards.
- Standardized data governance policies to maintain accuracy and security.
Data Migration, Data Modernization & Integration
Seamless migration and integration of data across multiple environments.
- Smooth transition from legacy systems to modern data mesh architectures.
- Unified data ingestion ecosystem by integrating multiple data sources.
- Automated ETL/ELT workflows for minimal disruption and high efficiency.
Real-Time Data Processing Solutions
High-speed data streaming for instant insights and automated actions.
- Real-time data pipelines using Apache Kafka, Spark Streaming, and Flink.
- Event-driven architectures to process massive data streams.
- Automated monitoring and alerts for real-time decision-making with big data.
Machine Learning & Natural Language Processing (NLP)
AI-driven models that automate and enhance business intelligence.
- Machine learning solutions for fraud detection, customer insights, and automation.
- NLP-powered text analytics, chatbots, and sentiment analysis.
- Advanced AI frameworks including Hugging Face, SpaCy, and NLTK.
Data Engineering Consulting
Expert data strategy and hands-on support for building and optimizing your big data engineering infrastructure.
- In-depth assessment and refinement of existing data mesh architectures.
- Custom strategies to enhance data flow, ingestion, and collection across pipelines.
- Ongoing support to maintain scalable and future-proof data solutions.
Our Data Engineering Process
Understanding Business
and Data Requirements
- Analyze business goals, technical landscape, and data sources.
- Assess infrastructure, compliance needs, and scalability factors.
Data Source Analysis and Security Measures
- Evaluate existing and potential data sources (structured and unstructured).
- Identify integration opportunities and fill data gaps.
- Implement robust security policies, including access controls, encryption, and governance frameworks (GDPR, CCPA compliance).
Building Scalable Data Infrastructure
- Design and implement a scalable data lake (on-premise or cloud-based).
- Ensure efficient storage and retrieval of raw and processed data.
- Enable smooth integration with business systems (CRM, ERP) and standardize data formats.
 Data Pipelines and Automation
- Develop high-performance ETL/ELT workflows to collect, clean, and transform data.
- Optimize data flow for accuracy, consistency, and accessibility.
- Leverage DevOps for automated deployment, reducing manual intervention and ensuring system reliability.
Data Quality Assurance and Monitoring
- Validate data accuracy, integrity, and performance through rigorous testing.
- Use automated monitoring tools to detect anomalies and maintain ongoing data quality.
Reporting, Insights, and Continuous Improvement
- Create dashboards and reports for actionable insights.
- Empower non-technical users with intuitive visualization tools.
- Refine the data strategy based on stakeholder feedback to improve efficiency and scalability.
Contact us to design your robust, scalable data infrastructure today.
Our Data Engineering Process
Deep Discovery and Planning
- Deep dive into your business goals, audience, workflows, and tech requirements.
- Define project scope, timeline, and deliverables.
Strategy and Custom Web Design
- Create wireframes and prototypes to visualize the user journey.
- Design a custom, brand-aligned interface optimized for engagement.
Development
- Build a secure, scalable backend and a responsive frontend.
- Integrate APIs, third-party tools, and custom features.
Testing and Quality Assurance
- Conduct end-to-end testing for performance and functionality.
- Identify and fix bugs.
- Perform code reviews and audits.
Launch and Deployment
- Deploy your website or application in a secure environment.
- Ensure a smooth transition with minimal downtime.
Ongoing Support and Optimization
- Monitor performance and address evolving business needs.
- Implement iterative updates based on user feedback and analytics.
Contact us to build your web solution now.
Technologies We Use
Languages
Tools
Database
How to Work With Us
1
Join a call with our sales and technical team to discuss your data engineering needs, project scope, and engagement models.
2
Receive a tailored proposal outlining the project scope, pricing, and team structure.
3
Review and refine the proposal in a follow-up discussion to make sure it aligns with your business goals.
4
Once you approve, we’ll onboard your team of expert data engineers, analysts, and scientists to build and optimize your data infrastructure.
1
Join a call with our sales and technical team to discuss your data engineering needs, project scope, and engagement models.
2
Receive a tailored proposal outlining the project scope, pricing, and team structure.
3
Review and refine the proposal in a follow-up discussion to make sure it aligns with your business goals.
4
Once you approve, we’ll onboard your team of expert data engineers, analysts, and scientists to build and optimize your data infrastructure.
Engagement Models
Choose between two flexible engagement models to collaborate with us on short- or long-term data engineering projects:
Staff Augmentation
Agile Development Teams
Why Choose Distillery as Your Data Engineering Partner?
Elite Data Engineering Talent
Gain access to a highly skilled team of data engineers, analysts, and scientists who specialize in big data engineering and building and optimizing large-scale data infrastructures.
Cost-Effective Data Solutions
Leverage nearshore data engineering expertise at competitive rates with our strategically located teams in Latin America. Reduce the costs and challenges of building an in-house data team while maintaining high-quality results.
Customized Data Solutions
Our tailored big data engineering and analytics solutions give your business a competitive edge.
Enterprise-Grade Security
We prioritize data protection with advanced encryption, strict access controls, and continuous security assessments.
Agile & Adaptive Execution
Accelerate your data engineering projects with agile methodologies that promote flexibility, transparency, and iterative improvements.
Scalable Data Infrastructure
From efficient ETL pipelines to flexible cloud architectures, our solutions adapt to growing data volumes and business complexity.
FAQ
How much do custom data engineering services cost?
We offer flexible pricing models for custom data engineering services, whether you’re looking for data pipeline development, cloud data architecture, or ongoing data infrastructure support and maintenance.
We will provide a detailed data engineering proposal outlining the scope of work, team composition, timeline, engagement model, and ongoing support. This gives you full transparency into our pricing.Â
Are there additional costs for post-launch changes or issues?
Our data engineering services include ongoing maintenance tasks like bug fixes, security patches, and minor updates. However, major updates, such as adding a new data source, scaling infrastructure, or making significant changes to your data pipelines, may incur additional costs.
We offer flexible support options, so you only pay for services that deliver real value to your data infrastructure.
What kind of team will Distillery assemble for data engineering projects?
Based on your project requirements, we will assemble a dedicated team of experienced data professionals, including:
- Data Engineers
- Data Architects
- Data AnalystsÂ
- Data ScientistsÂ
- Cloud EngineersÂ
- DevOps Specialists
- QA EngineersÂ
- Project ManagersÂ
Can I scale the data engineering team based on project needs?
Yes, scaling your data engineering team with us is simple and flexible.Â
If you need additional resources, we can quickly onboard skilled data professionals, including a data engineer, cloud specialist, and data scientist, to meet project demands. If your project scope decreases, we can scale back the team accordingly without disrupting your project.
How will you ensure smooth communication during the data engineering service?
- A dedicated project manager will be your primary point of contact throughout the project, ensuring clear and consistent communication.Â
- Our data engineering team will integrate seamlessly with yours, providing regular progress updates and participating in all key meetings.
- We will identify potential project risks early and share action plans during regular update sessions.Â
- For quick queries, you can reach out via Slack, email, or your preferred communication tool.
How secure is my enterprise data when leveraging Distillery’s data science or engineering services?
Data security is a top priority. We implement industry-leading security protocols, encryption techniques, and compliance practices to protect your data at every stage — during transfer, processing, and storage. We safeguard against unauthorized access and data breaches with the following measures:
- Data Encryption: We encrypt data both in transit and at rest to prevent unauthorized access.
- Access Controls: We implement strict access controls so that only authorized personnel can access sensitive data.
- Compliance: We adhere to relevant data protection regulations (e.g., GDPR, CCPA) to maintain compliance.
- Monitoring and Auditing: We use advanced monitoring tools to track data access and conduct regular audits to identify and address vulnerabilities.
How do you incorporate AI into your data science and engineering services?
AI enhances our data engineering services by automating data processing and improving the accuracy of analytics. AI models help to identify patterns, predict trends, and support real-time decision-making by processing large volumes of data faster and more efficiently.
We also integrate AI technologies like machine learning and predictive analytics to optimize data pipelines, generate valuable insights, and improve overall business performance.
Can you handle both structured data and unstructured data?
Yes, we specialize in managing both structured data and unstructured data. We can build data pipelines that handle all data types efficiently—relational databases, streaming data, or raw files.Â