Build Robust and Scalable Data Engineering Solutions

Data engineering provides the essential infrastructure and automated pipelines that convert raw information into a reliable strategic asset. While data science and BI focus on analysis and visualization, data engineering handles the vital fundamentalsโ€”the underlying architecture and delivery systems that ensure data is secure and accessible. Our data engineering services bridge the gap between fragmented data and actionable intelligence for both startups and Fortune 500 enterprises.

With over 30 years of experience, we provide turnkey data engineering solutions that resolve the challenges of limited in-house expertise and inefficient legacy systems. We work closely with you to design and install modern data architectures tailored to your specific cloud or on-premise environment. By utilizing AI-powered approaches, industry best practices, and modern governance practices, our data engineering services eliminate operational silos and transform chaotic historical data into a structured, protected asset that drives precision and productivity.

Strategic Benefits of Our Data Engineering Solutions

Our end-to-end data engineering services move beyond basic data management to provide a competitive edge through:

  • Innovation icon

    Innovation

    Build a flexible foundation that accelerates R&D cycles, enabling the integration of new technologies twice as fast as legacy environments.

  • Faster Insights icon

    Faster Insights

    Accelerate decision making with high-speed pipelines that reduce data latency by up to 80%, delivering real-time, analysis-ready information.

  • Intelligent Automation icon

    Intelligent Automation

    Reduce manual data handling and operational overhead by 40% through AI-powered workflows and automated data processing.

  • Security icon

    Data Security and Governance

    Protect your valuable assets with built-in encryption, access controls, and compliance-first architecture.

  • Improved Efficiency icon

    Improved Efficiency

    Lower your total cost of ownership (TCO) by 25โ€“30% by eliminating redundant storage and optimizing cloud resource consumption.

  • Seamless Scalability icon

    Seamless Scalability

    Future-proof your business with elastic infrastructure designed to grow seamlessly in tandem with your data volume.

Ready to align your data strategy with business goals?

letโ€™s talk   

Data Engineering Services

Data Architecture and Data Modeling

Our data teams designs scalable, resilient architectures utilizing event-driven ingestion pipelines and low-latency retrieval APIs. By leveraging robust ETL/ELT workflows, we ensure high-integrity data processing that serves as the foundation for actionable insights. From optimizing legacy frameworks to architecting new systems from the ground up, we deliver high-performance data engineering solutions tailored to your operational needs.

Data Migration

We help you seamlessly transition your sensitive data across any environmentโ€”whether moving from on-premise to the cloud, between cloud providers, or across disparate enterprise platforms. Our engineers conduct a deep assessment of your data environment and business objectives to ensure a smooth, secure migration that minimizes operational downtime.

Data Storage

Our data specialists design and build secure, scalable storage architectures tailored to your specific data types and business objectives. Whether deploying a data lake for raw, unstructured data or a data warehouse to consolidate disparate sources, we engineer systemsโ€”across cloud and on-premise environmentsโ€”that eliminate silos and ensure high-performance access.

Data Analytics

Our data engineering consultants transform complex, unstructured data streams into refined, analytics-ready formats, serving as a single source of truth for your company. This way, we pave the way for end-to-end analysis that reveals the trends and patterns essential for a competitive advantage. With a core focus on scalability, our data analytics engineering services ensure that your data environment grows in tandem with your business, meeting the demands of both current operations and future growth.

Data Integration

We help bridge the gap between fragmented data sources by integrating data from multiple sources into a single, cohesive environment using robust ETL or ELT pipelines. This seamless consolidation transforms disparate datasets into a unified strategic asset, removing the complexities of managing diverse data origins. As a result, you gain the clarity required to drive more precise and efficient decision making across all departments.

Data Governance

Our specialists establish robust data governance frameworks to ensure that your data remains accurate, reliable, and protected. By evaluating your current policies and implementing time-tested management standards, we define clear ownership and stewardship for your data assets. This structured approach eliminates mismanagement and optimizes data flow, providing a reliable foundation of high-quality information for your entire organization.

Real-time Data Streaming and Analytics

Our data engineers build streaming environments that ingest, clean, and deliver information as it occurs, ensuring your stakeholders work with the most current data available. By integrating advanced stream-processing frameworks, we provide a foundation for live dashboards and automated responses that keep your organization ahead of market shifts.

Data Security and Compliance

Our cybersecurity experts fortify your data infrastructure with multi-layered security protocols to mitigate sophisticated cybersecurity threats and prevent unauthorized access. We safeguard your information assets at all times by architecting resilient security layers and implementing granular access controls. Our deep domain expertise ensures that every solution meets industry standards, including GDPR and HIPAA, providing a compliant foundation for data-driven growth.

Data Quality Management

Our team helps ensure your data environments maintain peak quality throughout the entire data lifecycle, from raw capture to final analysis. Through advanced observability and continuous assessment, we identify and resolve anomalies before they impact your decision-making processes. By safeguarding data validity and completeness, we transform raw inputs into trustworthy, high-value assets that seamlessly integrate with your broader enterprise ecosystem.

DataOps

We deploy advanced DataOps architectures to unify the development and production life cycles of your data ecosystem. By integrating automated CI/CD pipelines with high-level orchestration, we ensure that your infrastructure supports rapid, low-risk deployment and consistent high availability. This methodology replaces manual, fragmented workflows with a resilient, automated environment that delivers mission-critical data products with absolute integrity.

Big Data

We design big data solutions that convert complex, high-volume datasets into a unified strategic advantage. As part of big data engineering services, we assess your current data maturity and pinpoint optimization opportunities within your pipelines and storage frameworks. NIX develops and manages a robust data infrastructure tailored to your organizational capacity, ensuring your ecosystem is engineered for both immediate impact and long-term scalability.

NIX Solves Your Most Complex Data Challenges

Fragmented data and legacy limitations shouldn’t stall your growth. Our data engineering services help you bridge the gap between technical debt and operational excellence.

  • High Operational and Storage Costs

    Optimize data storage strategies and streamline pipeline efficiency to reduce redundant processing and lower overall infrastructure expenses.

  • Data Silos Across Departments

    Unify disparate sources into a single, coherent environment to enable cross-functional analytics, facilitating faster and synchronized decision-making.

  • Inconsistent or Poor Data Quality

    Apply automated cleansing and validation frameworks to standardize formats and enforce quality rules, ensuring that your teams work with accurate and reliable datasets.

  • Slow and Unreliable Reporting

    Modernize infrastructure with automated ETL techniques and orchestration tools to ensure data arrives on time, every time, to power your business intelligence.

  • Scalability Limits of Legacy Systems

    Migrate restrictive legacy setups to elastic, cloud-native platforms to ensure your infrastructure performance stays ahead of increasing data volumes.

  • Real-time Processing Limitations

    Deploy streaming ingestion pipelines to capture, enrich, and deliver live data, allowing you to respond instantly to operational events.

Data Engineering Solutions

Data Lakes and Data Warehouses

Our experts design and optimize data lakes and warehouses to streamline the storage, management, and analysis of enterprise-scale information. Leveraging partnerships with AWS, Google Cloud, Azure, and IBM, we deliver secure, scalable environments that optimize storage costs and processing speed. Whether building a warehouse from scratch or modernizing an existing system, we deliver resilient, scalable architectures that eliminate the overhead and complexity of legacy environments.

Data Lakes and Data Warehouses

ETL/ELT Development

NIX engineers develop high-performance data pipelines that support end-to-end ETL/ELT workflows across cloud and legacy infrastructures. Our experts bridge technical gaps by integrating REST APIs and proprietary systems into a scalable, automated framework. Whether via batch or real-time processing, we deliver streamlined data integration tailored to enterprise-scale requirements.

ELT Development

Data Fabric

We implement full-fledged data fabric solutions to automate discovery and facilitate seamless integration across heterogeneous platforms. This distributed architecture supports diverse governance and operational requirements, ensuring the delivery of resilient data to business users. By optimizing the data value chain through automation, we enable self-service consumption and improve organizational agility in high-volume environments.

Data Fabric

Real-time Data Pipelines

At NIX, we build high-velocity data pipelines that consolidate information from disparate sources using ETL and ELT methodologies. By implementing stream processing and automated ingestion, we provide a single source of truth that enables instantaneous, data-informed decision making. These resilient solutions eliminate latency in reporting and ensure your business operates on real-time, high-fidelity data, regardless of volume or velocity.

Real-time Data Pipelines

Contact us to discuss your big data needs

Contact us   

Cloud for Data Engineering

  • Scalability

    Effortlessly handle exponential data growth and fluctuating workloads with an elastic infrastructure that expands alongside your business.

  • Flexibility

    Adapt quickly to market shifts by integrating the latest tools and technologies into an agile, vendor-agnostic environment.

  • Cost Optimization

    Reduce operational overhead by paying only for the resources you use through intelligent automation and resource management.

  • Data Accessibility

    Break down silos and empower your teams with secure, high-speed access to a unified source of truth across the enterprise.

AI for Data Engineering

  • Automation

    Eliminate repetitive tasks by deploying AI-driven pipelines that handle data ingestion, transformation, and orchestration without manual intervention.

  • Efficiency

    Accelerate your time to insight with intelligent resource allocation and query optimization that maximize throughput while reducing latency.

  • Enhanced Quality

    Ensure data integrity through AI-powered observability that automatically detects anomalies, repairs inconsistencies, and prevents data drift.

  • New Capabilities

    Unlock advanced opportunities like predictive scaling, automated metadata generation, and natural language data discovery to stay ahead of the competition.

Relevant Case Studies

We really care about project success. At the end of the day, happy clients watching how their application is making the end userโ€™s experience and life better are the things that matter.

View all case studies

Navigating the Cloud: Modernization of Healthcare Data Pipelines

Healthcare

Success Story Navigating the Cloud: Modernization of Healthcare Data Pipelines image

Predictive Models Development to Support Clinical Decisions

Healthcare

Success Story Predictive Models Development to Support Clinical Decisions image

DaaS Platform for the Educational Ecosystem

Education

Success Story DaaS Platform for the Educational Ecosystem image

Enterprise Data Warehouse Reinforcement for Insurance Company

Insurance

Success Story Enterprise Data Warehouse Reinforcement for Insurance Company image

Cloud Analytics for Retail Chain

Retail and E-commerce

Success Story Cloud Analytics for Retail Chain image

ML System for Real-time Bidding

Marketing & Advertising

Success Story ML System for Real-time Bidding image
01

Data Engineering Process and Methodology

We follow a flexible, engineering-driven life cycle to ensure your data infrastructure is scalable, secure, and aligned with your strategic objectives:

1

Define Business Goals

We align with your vision to map critical data workflows and define a precise scope of work that prioritizes your core business objectives.

2

Set Up Data Collection

Our team audits diverse sources to ingest data—structured and unstructured, designing custom APIs and secure protocols to ensure seamless, high-integrity data exchange.

3

Data Pre-processing

We cleanse and transform raw inputs, implementing rigorous quality controls and selecting the optimal tech stack for your specific use case.

4

Architect Data Storage

We build secure, scalable storage environmentsโ€”tailored to your data volumeโ€”that ensure high availability for authorized users and systems.

5

Business Integration

Our engineers deploy your solution into the production environment, ensuring it meets strict performance and data accuracy thresholds under real-world loads.

6

Validation and Optimization

We establish continuous monitoring to assess system throughput and precision, making iterative adjustments to maintain peak efficiency.

Data Engineering Engagement Models

At NIX, we offer flexible engagement models designed to align with your projectโ€™s maturity, technical complexity, and organizational goals.

  • Navigate the complexities of modern data landscape with a customized strategy tailored to your operational needs. We provide data engineering consulting services for infrastructure optimization, stack selection, data integration tools and advanced analytics to ensure your data ecosystem is scalable and aligned with long-term business objectives. Our experts focus on building the foundational roadmap and selection of tools required to efficiently process data, turning raw inputs into predictive assets that scale with your growth.

  • Offload the complexity of your data life cycle to our specialized teams. We provide turnkey managementโ€”from initial infrastructure audits and architectural design to implementation and ongoing maintenance. This model allows you to focus on core business drivers while we deliver fully optimized, resilient data engineering solutions tailored to your needs.

  • Rapidly scale your internal capacity with specialized data engineers who integrate directly into your agile workflows. We provide the niche talent required to eliminate bottlenecks and accelerate your time to insight without the overhead of permanent hiring.

  • consulting icon

    Consulting

    Navigate the complexities of modern data landscape with a customized strategy tailored to your operational needs. We provide data engineering consulting services for infrastructure optimization, stack selection, data integration tools and advanced analytics to ensure your data ecosystem is scalable and aligned with long-term business objectives. Our experts focus on building the foundational roadmap and selection of tools required to efficiently process data, turning raw inputs into predictive assets that scale with your growth.

  • End-to-end Data Engineering icon

    End-to-end Data Engineering

    Offload the complexity of your data life cycle to our specialized teams. We provide turnkey managementโ€”from initial infrastructure audits and architectural design to implementation and ongoing maintenance. This model allows you to focus on core business drivers while we deliver fully optimized, resilient data engineering solutions tailored to your needs.

  • Data Engineering as a Service icon

    Data Engineering as a Service

    Rapidly scale your internal capacity with specialized data engineers who integrate directly into your agile workflows. We provide the niche talent required to eliminate bottlenecks and accelerate your time to insight without the overhead of permanent hiring.

What You Get With NIX

  • Rapid Start of Deployment

    3000+ experts with a 10% talent pool for ongoing project needs.

  • 360-degree Approach

    We listen first and build secondโ€”exploring every angle and uncovering all potential solutions to pinpoint the best-fitting one.

  • One-stop shop

    From strategy and planning to market-ready solutions, ongoing support, enhancements, and promotion.

  • Executive Level Support

    Strategic agility, rapid escalations, and hands-on leadershipโ€”your project moves forward without bottlenecks.

  • Involvement and Versatility

    We take delivery ownership of every project, driving measurable impact beyond just execution.

  • Industry Recognition

    Our strategic alliances with AWS, Microsoft, Databricks, and GCP translate into state-of-the-art technical solutions and conditions for your business.

  • Seasoned Expertise

    Decades-honed expertise across various domains and thousands of projects translates into solutions that hit the mark.

  • Mature and Transparent Processes

    Our time-tested delivery process drives results, fosters team alignment via consistent communication, and remains adaptable to new challenges.

Bridge your technical gaps with specialized expertiseโ€”contact us to extend your data engineering team.

letโ€™s talk   

What Our Clients Say

Buzz Sharifi photo

Buzz Sharifi

Account Manager at TransGrade, CRM

Matthew Brown photo

Matthew Brown

VP of Engineering at Elsevier

Christian Rohner photo

Christian Rohner

Project Manager at Information Products AG

Jeremy Barron photo

Jeremy Barron

Senior Director of Engineering at Premier

Craig Burris photo

Craig Burris

Director of Operations at CarSoup

Jason Scalvini photo

Jason Scalvini

Senior VP of Technology

Ilya Kottel photo

Ilya Kottel

VP R&D at HumanEyes

Noam Shalit photo

Noam Shalit

COO at SafeRide Technologies Ltd

Steve Berardelli photo

Steve Berardelli

Sr. Director of Engineering for MindTap

Moody Heard photo

Moody Heard

Co-Founder at Buildforce

Mike Ortner photo

Mike Ortner

President at Ortner Enterprises DBA North Two Five

Mark DeJarnatt photo

Mark DeJarnatt

Chief Technology Officer at Sparkle Stories LLC

Eric Spear photo

Eric Spear

SVP of Engineering at Cengage

Jeremy Reither photo

Jeremy Reither

Consultant & Advisor at DemandSide

Eve Epstein photo

Eve Epstein

CEO/Founder at SoleVenture, Inc.

David Stutzman photo

David Stutzman

President of Conspectus, Inc

Dave Kochalko photo

Dave Kochalko

Co-Founder & CEO at ARTiFACTS

Kevin Lee photo

Kevin Lee

Co-Founder

Norman Thiem photo

Norman Thiem

Owner, N2 Plus

Ariel Orbach photo

Ariel Orbach

Co-Founder & CTO

Anonymous photo

Anonymous

CTO, Real Estate Firm

Anonymous photo

Anonymous

Founder & HOP, Fitness Space Rental Platform

Anonymous photo

Anonymous

CTO, Color My Life, Inc

Anonymous photo

Anonymous

Department Head, Fignum Limited

Data Engineering Technology Stack

  • python logo
  • scala-stack logo
  • java icon
  • kafka
  • apache spark
  • hadoop-stack-icon
  • apache-stack-icon
  • cassandra-stack-icon
  • sql server
  • php
  • ibm-db2
  • mongoDB
  • elastic-stack-icon
  • liquibase-stack-icon
  • presto logo
  • dbt logo
  • scrapy logo
  • apache-beam
  • apache-hudi logo
  • delta-lake logo
  • Snowflake logo
Max Ushchenko

Max is our senior practice leader and evangelist for the โ€œbig triadโ€ of machine learning, data analytics and data engineering, with a vast background in AI, BI services, and product management.

Head of Data and AI Practice at NIX

Max is our senior practice leader and evangelist for the โ€œbig triadโ€ of machine learning, data analytics and data engineering, with a vast background in AI, BI services, and product management.

Eugene Rudenko

Yevhen, a seasoned AI consultant with 10+ years, delivers expert-level software optimization and business automation through strategic implementation of cutting-edge AI solutions.

Applied AI & Data Science Solutions Consultant

Yevhen, a seasoned AI consultant with 10+ years, delivers expert-level software optimization and business automation through strategic implementation of cutting-edge AI solutions.

01

FAQs on Data Engineering Services

01/

How much do data engineering services cost?

Data engineering services typically involve a wide pricing range depending on project scope, complexity, and data volume, with hourly rates generally falling between $50 and $150 USD. While a targeted data engineering consulting engagement typically starts at around $5,000 for an initial audit, a comprehensive enterprise modernization project can range from $25,000 to $150,000 or more. These costs are primarily driven by the complexity of your data sources, the volume of processing required, and the level of automation needed to sustain your operations.

02/

How do you ensure data security and compliance?

Our data engineers integrate security directly into the pipeline architecture using a security-by-design approach that includes end-to-end encryption and granular access controls. We leverage data engineering capabilities to automate compliance auditing, ensuring your environment consistently meets rigorous standards, such as GDPR and HIPAA. By combining proactive monitoring with secure data masking, we protect your information assets from unauthorized access while maintaining the transparency required for regulatory peace of mind.

03/

Can you help us integrate data from multiple sources?

Yes, our data engineers build automated pipelines that consolidate information from REST APIs, legacy databases, and cloud applications into a holistic 360-degree view of your business. We specialize in high-throughput data integration solutions that synchronize disparate datasets, eliminating silos and providing a unified view of your entire business operation.

04/

Can you help migrate legacy data systems to modern cloud platforms?

Yes, we provide end-to-end migration services to transition your on-premise systems to scalable cloud environments, such as AWS, Azure, and Google Cloud. Our data engineering consulting ensures a low-risk transition that preserves data integrity and minimizes business downtime.

Migrating to the cloud reduces your maintenance costs and allows your data infrastructure to scale instantly as your business grows.

05/

What are the key considerations for modernizing data platforms?

Key considerations should include DataOps automation and cloud-native scalability to eliminate manual bottlenecks and technical debt. Modern platforms must prioritize data observability, using AI to proactively detect anomalies and ensure the health of your pipelines. By architecting for interoperability and adopting open standards, you prevent vendor lock-in and ensure your data remains accessible and cost-optimized as your volume grows.

06/

What measures do you take to ensure data quality and governance?

We maintain the highest standards of data integrity by deploying automated observability tools that monitor for accuracy, completeness, and validity in real time. Our data engineering consulting team establishes formal governance frameworksโ€”including clear data ownership and lineage trackingโ€”to ensure your information remains trustworthy and audit-ready. In summary, these measures prevent data degradation and ensure that your business decisions are always based on precise, high-fidelity information.

07/

What is data engineering, and why is it important?

Data engineering is the practice of designing and building systems that collect, store, and transform raw data into high-quality information for analysis. For your business, this means moving beyond simple data collection to creating a reliable infrastructure that scales with your growth and supports advanced data engineering capabilities. By investing in professional data engineering services, your organization gains a competitive edge through accelerated time to insight, reduced operational costs, and the technical maturity required to power AI and predictive analytics with complete confidence.

Contact Us

Accessibility Adjustments
Adjust Background Colors
Adjust Text Colors