Data Engineering Services

Turning data chaos into insight harmony.

Our data engineering and ETL services are designed to optimize your data infrastructure with advanced ETL pipelines and scalable data lakes. We implement data extraction using APIs, message queues, and CDC (Change Data Capture) techniques, followed by transformation through Spark, Python, and SQL-based processing. Our solutions ensure efficient data loading into cloud-based data warehouses like AWS Redshift, Google BigQuery, and Snowflake. With automated orchestration using tools like Apache Airflow and Prefect, we ensure seamless data flow, high availability, and real-time analytics readiness.

Bridge the gap between raw data and actionable intelligence. Discover how our ETL services can enhance your analytics.

We help you solve
your pressing challenges.

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Our Complete Suite of Data Engineering Services

Data drama? We help you get rid of it, in nice way!

Data Architecture & Pipeline

We craft scalable architectures using microservices, data lakes, and real-time streaming with Apache Kafka and Flink. Our pipelines are optimized for performance, handling complex ETL processes with precision and speed. Whether you're managing massive data sets or ensuring smooth data governance, we make sure your architecture is future-proof and ready to grow with your business needs.

Data Lake Design and Implementation
Real-time Data Streaming and Integration
ETL Pipeline Development and Optimization
Data Pipeline Orchestration

DataOps Managed Services

We handle the end-to-end management of your data pipelines, from orchestration with Apache Airflow to monitoring with Grafana and Prometheus. Our team ensures continuous integration and delivery of data solutions, minimizing downtime and maximizing efficiency. With proactive incident management and performance optimization, we keep your data operations running smoothly.

Pipeline Orchestration and Automation
CI/CD for Data
Real-time Monitoring and Alerting
Performance Tuning and Optimization

Data Governance

We implement robust frameworks for data quality, integrity, and privacy using tools like Apache Atlas and Collibra. Our approach includes defining data ownership, establishing clear data policies, and enforcing access controls. With real-time monitoring and auditing, we help you maintain regulatory compliance while enabling trustworthy data management.

Metadata Management and Data Cataloging
Data Ownership and Stewardship
Data Access Control and Security
Regulatory Compliance Audits

Big Data Analytics

We leverage technologies like Hadoop, Spark, and distributed databases to process and analyze massive data sets with speed and accuracy. From real-time data streaming to complex predictive modeling, we provide actionable insights that drive strategic decisions. With our expertise, you can transform big data challenges into opportunities for growth and innovation.

Data Processing with Hadoop and Spark
Real-time Data Analysis and Visualization
Data Warehousing and OLAP
Machine Learning and Advanced Analytics

Wondering how to build scalable, reliable data pipelines? Get a ballpark estimation within 36 hours.

What’s Trending Now!

Discover the forefront of data engineering. Stay agile and competitive with real-time processing and automated data quality enhancements.

Decentralized data architecture for distributed data ownership.
Combination of data engineering and DevOps.
Embedding machine learning models directly into ETL pipelines.
Employing AI-driven solutions for automatic data quality checks.

Data Engineering Support: From Strategy to Success & Beyond

After your data engineering and ETL solutions are in place, our support team becomes your go-to partner for seamless operations and innovation. We provide proactive maintenance, rapid troubleshooting, and ongoing optimization.

Support for scaling data infrastructure/pipelines as data volumes grow.
Assistance with integrating new data sources into existing pipelines.
Strategies and support for data recovery and system restoration.
Configurable alerts for monitoring pipeline health, data anomalies.

Explore the Possibilities with Our Data Engineering Services

Enhanced Data Integration

Data engineering and ETL services make it easy to pull together all your disparate data sources—whether they're old systems or modern cloud apps—into a single, coherent view. This unified approach helps you see the big picture and gain insights.

Improved Data Quality

It uses advanced techniques to clean and validate your data, ensuring it’s accurate and reliable. With high-quality data, you can trust your insights and make decisions with confidence. This means fewer errors and better results for your business.

Advanced Analytics Capabilities

With the right data engineering, you can unlock powerful analytics tools and machine learning models. This means you can dive deeper into your data, uncover trends, and make predictions that help you stay ahead of the competition.

Reduced Time-to-Insight

You can cut down the time it takes to turn raw data into actionable insights. By streamlining ETL processes and fine-tuning data pipelines, we ensure you get the information you need faster, so you can make timely decisions and stay ahead of the curve.

Technologies: The Engine Room

We constantly dig deeper into new technologies and push the boundaries of old technologies, with just one goal - client value realization.

Read Blog : Why Treat Data as a Product?

Why Azilen is the right choice

We deliver nothing less than excellence.

Team leading engineering excellence at Azilen

Case Studies: Real Transformations, Real Results

Explore how we've turned client challenges into measurable results.

The Spirit Behind Engineering Excellence

We instantly fall in love with your challenges and steal it from you!

400+

Product Engineers
15+

Years of Experience
100+

Delivered Lifecycles

10M+

Lives Touched
3M+

Man Hours Invested
10+

Wellness Programs

What Our Clients Say About Their Journey with Us

The essence (in case you don't read it all): We nail it, every time!

Dave Stevens

CTO | Fulcrum

In the rapidly evolving world of technology, finding a reliable software development partner is like finding a needle in a haystack. But with Azilen, we found a team that constantly seeks to understand our complex environment and requirements while translating them into practical, efficient solutions.
Their team of skilled developers has consistently delivered high-quality software. Their ability to adapt to changes and provide innovative solutions has greatly contributed to our success.
We are satisfied with our partnership with Azilen and look forward to achieving greater milestones together.

Jona Boeddinghaus

COO | Gradient Zero

The Azilen team helped develop a complex cross-platform mobile application. We were more than happy with the professional project management and transparent communication. Scoping and implementation were as easy as working with local staff. The results delivered were always on time and of high quality. We look forward to working with Azilen on our next project.

Matt Venturi

CEO | ClearingBid Inc.

We appreciate our relationship with Azilen. We are just getting going, ClearingBid is going to democratize the IPO market for all, this is where Azilen has helped and played an important role with us. For a big vision, we did not have a design team to start, so number of our solutions were driven by Azilen. I want to give a big shout out the structured product management skills and the necessary follow up efforts from the team.

Svend Bøe

CEO | Veng Norge

We are extremely satisfied with the competence technical expertise that Azilen has shown us, this is combined with great customer service.

Product Engineering is in Our DNA.

And we are not a development outsourcing company!

THE AZILEN Promise	Upheld
Product Lifecycle Management
Strategic Innovation and R&D
Cross-Disciplinary Expertise
Product Ownership and Vision
Scalable Architecture Design
Agile and Iterative Development
Long-Term Strategic Partnerships

Frequently Asked Questions (FAQ's)

Get your most common questions around Data Engineering services answered.

What is data engineering, and why is it important for software products?

Data engineering involves designing, building, and maintaining the systems and infrastructure that allow organizations to collect, store, and analyze data efficiently. For software products, effective data engineering ensures that data is accessible, reliable, and actionable, enabling better decision-making, enhanced product features, and improved user experiences.

What are the key components of a data engineering service?

Key components typically include data ingestion, data processing, data storage, data integration, and data orchestration. Data engineers work on creating pipelines that move data from various sources to storage systems, transforming and cleaning the data along the way to ensure it is usable for analysis and reporting.

What types of data sources can be integrated into a data engineering pipeline?

Data sources can include relational databases, NoSQL databases, data warehouses, APIs, cloud storage services, and external data feeds. Data engineering services can integrate data from various sources, including structured and unstructured data, to create a comprehensive data ecosystem.

What are the common challenges in data engineering, and how are they addressed?

Common challenges include handling large volumes of data, ensuring data quality and consistency, managing data integration from diverse sources, and maintaining system performance and scalability. Data engineering services address these challenges through robust architecture design, data validation techniques, and efficient data processing frameworks.

How does data engineering differ from data science, and how do they work together?

Data engineering focuses on building the infrastructure and pipelines required to collect, store, and process data, while data science involves analyzing and interpreting that data to extract insights and build predictive models. Both disciplines work together, with data engineering providing the foundation for data science to perform meaningful analysis.

What is ETL, and why is it important in data engineering?

ETL stands for Extract, Transform, Load. It is a critical process in data engineering where data is extracted from various sources, transformed into a usable format, and then loaded into a data warehouse or database. This process ensures that data is cleansed, standardized, and integrated for analysis and reporting.