Data Engineering Services

Let Us Engineer Your Data with Smart, Scalable Data Engineering Solutions

Building smarter data pipelines for data at rest and data in motion, Our Data Engineering services ensure your data is reliable, accessible, and analytics-ready, driving faster, smarter decisions across the enterprise.

Request for Consultation

Why Data Engineering Matters?

Slow Processes

Slow Processes

Outdated data systems can slow decision-making, leading to missed opportunities. Inefficient data storage and retrieval mechanisms cause lag, preventing businesses from making real-time decisions. Data engineering services streamline these processes for faster, efficient decision-making.

Complex pipelines

Complex pipelines

Unstructured data flows create bottlenecks, making data management chaotic and error prone. As data volume and velocity grow, scaling these data pipelines becomes a challenge. It demands advanced data engineering architectures designed for performance, scalability, and flexibility.

Siloed systems

Siloed systems

Disconnected data sources hinder teams from accessing critical insights, reducing collaboration. Business intelligence and data analytics suffer as teams struggle to gain a unified view of operations. Effective data engineering helps unify and connect data sources for streamlined insights.

Our Core Offerings in Data Engineering Services

Smart ETL/ELT Pipelines

Automate data extraction, transformation, and loading (ETL) for seamless integration with minimal manual intervention.

Data Lakes and Warehouses

Securely store both structured and unstructured data in scalable environments for easy access and advanced data analytics.

Real-Time Real-Time

Deliver instant data updates to enable immediate insights and proactive decision-making with real-time data pipelines.

Consumption-Ready Data for Analytics

Prepare and optimize data to be cleansed, enriched, and ready for actionable insights without additional processing.

AI Integrated Data Integration

Use AI-powered data integration to intelligently connect diverse data sources, enhancing accuracy and predictive capabilities.

Data Quality & Data Lineage

Ensure trustworthy data with robust quality checks and transparent tracking for full traceability and compliance.

Empowering Your Business with Expert Data Engineering Services

Our data engineers are experts at building scalable, high-performance data solutions tailored to your business needs. With deep experience in modern data stacks, we design, develop, and maintain data pipelines that ensure reliability, speed, and accuracy across your organization.

Data Integration

-

Open-Source Data Integration

We specialize in data engineering using best-in-class open-source technologies for seamless, scalable data integration. Our expertise includes:

  • dbt: A SQL-first transformation framework for modular, version-controlled analytics.
  • Apache Airflow: Workflow orchestration for complex ETL pipelines, efficient scheduling, and managing dependencies.
  • Apache Kafka: Real-time data ingestion and event-driven architectures for scalable, distributed streaming.
  • Apache NiFi & Luigi: Low-latency tools for flexible data flows, supporting diverse integration scenarios and robust processing pipelines.
dbt
nifi
airflow
Luigi
kafka

ETL & Orchestration

+

Cloud-Native ETL & Orchestration

Our leading data engineering company specialize in serverless, cloud-native data consulting solutions that enable easy scalability, fast processing, and real-time analytics.

  • Azure Data Factory: Serverless integration at scale with pipeline orchestration across Azure’s vast ecosystem.
  • Amazon Glue: Fully managed ETL platform for data
    discovery, transformation, and cataloging in AWS.
  • Google Cloud Dataflow: Unified stream and batch processing, with auto-scaling and windowing for optimized real-time analytics.
  • AWS Data Pipeline & Step Functions: Seamless automation of data workflows, integrating custom jobs and ensuring efficient processing within the AWS ecosystem.
Azure-Data-Factory
Amazon-Glue
Google Cloud Dataflow
AWS-Data-Pipeline
aws

ETL Frameworks & Programming

+

Custom ETL Frameworks & Programming

We offer customized data solutions using a range of programming languages and frameworks to meet your unique needs.

  • Python-based Pipelines: Tailored data ingestion and transformation using Pandas, PySpark, or custom logic to meet specific needs.
  • Scala & Java: High-performance ETL solutions built on Spark/Hadoop clusters, ensuring fast processing for large-scale datasets.
  • Node.js & Go: Event-driven microservices that integrate with third-party APIs or real-time data streams, enabling custom, scalable solutions.
spark apache
go
pandas
node-js
java
Python
Scala

Data Lake & Warehouse

+

Data Lake & Warehouse Ecosystems

As a top-tier data engineering company, we provide expertise in modern data storage and analytics platforms helps organizations centralize and analyze data at scale.

  • Snowflake, Amazon Redshift, Google BigQuery, Azure Synapse: Industry-leading cloud platforms that enable centralized, high -performance analytics.
  • Databricks: Collaborative data engineering, analytics, and AI platform built on Delta Lake for unified analytics at scale.
  • Traditional SQL & NoSQL: Expertise in relational and non-relational databases like PostgreSQL, MongoDB, and Cassandra for diverse storage requirements.
google -big query
postresql
databricks
nosql
azure-synapse
mongo-db
Amazon-Redshift

Orchestration & Deployment

+

Orchestration & Deployment

We ensure your data engineering solutions are scalable, portable, and easily deployable.

  • Containerization: Using Docker and Kubernetes to create portable, reproducible components for your data pipeline.
  • Infrastructure as Code: With Terraform and CloudFormation, we automate and ensure consistent provisioning of cloud environments.
  • CI/CD Pipelines: We integrate continuous testing and deployment using GitHub Actions, Jenkins, and Azure DevOps, ensuring your data engineering workflows are agile and reliable.
jenkins
docker
cloudformation
azure-devops
github
kubernetes
Terraform

Our Data Engineering Case Studies

Automating Account Receivables for a Ratings Company and Leading Services

Challenge

-
Our client faced significant challenges with fragmented data sources across multiple systems, leading to inconsistent reporting and delayed decision-making. The existing manual processes were time-consuming and prone to errors, while the lack of real-time data visibility hindered operational efficiency.

Solution

+

Result

+
Know More

Process Automation

Data Integration

Accuracy Improvement

Compliance Boost

Why Choose Stryv.ai for Data Engineering?

As a leading data engineering company, Stryv.ai delivers comprehensive consulting services tailored to your specific business needs. Our team of expert data engineers specializes in building robust data pipelines and modern data lakes that support your digital transformation.

Whether you're looking for cloud data modernization, seamless data science integration, or scalable data engineering software solutions, we are here to guide you through every step of your data journey.

Let's Talk

Frequently Asked Question's

Data Engineering is the process of designing, building, and maintaining systems that collect, store, and process data for analysis. This involves creating data pipelines, integrating various data sources, transforming data into usable formats, and ensuring data quality and security.

  • Improved Decision-Making: With optimized data pipelines, you can access real-time insights and make informed decisions faster.
  • Scalability: Cloud-based solutions offer scalable data storage and processing, adapting to growing data needs.
  • Data Quality & Accuracy: Automated data validation ensures the accuracy and integrity of your data, enabling better analytics.

Data engineering services help build and manage scalable, secure data infrastructures, integrating data from multiple sources for easy access. They ensure your data is ready for analysis, enabling faster decision-making and improved operational efficiency.

As a trusted data engineering company, we use industry-leading tools and technologies, including

  • Apache Airflow for orchestrating ETL workflows. 
  • Apache Kafka for real-time data streaming. 
  • dbt for data transformation. 
  • Cloud Platforms like AWS, Azure, and Google Cloud for data storage and processing. 
  • Python and Scala for custom data solutions.

ETL stands for Extract, Transform, and Load, and it is a fundamental process in data engineering used to move and process data from various sources into a storage system like a data warehouse or data lake.

While data science focuses on analyzing and interpreting data to gain insights, data engineering is about building the infrastructure to collect, store, and process data. In essence, data engineering ensures that data is clean, accessible, and usable for data scientists to analyze.

Cloud data modernization involves transitioning from traditional on-premises data systems to cloud-based platforms. Our data engineering team can help with this by migrating your data to cloud-native storage solutions, optimizing data pipelines, and ensuring real-time access to data for seamless business operations.

Get in touch, and let's find the smartest way to move your project forward.

Learn more about Stryv's innovative services, designed to offer a modern, secure, and customized experience tailored just for you.

General enquiries

info@stryv.ai

Talk to Our Experts

+1-904-310-4540

Take Your First Step Towards Innovation!