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Data Engineering Services

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Data engineering services we provide

Data architecture
Data architecture

TechMagic’s data engineer consultant designs and optimizes your database and data warehouse platforms. We help you identify and integrate the right tools and technologies to ensure your data is accessible, accurate, and secure. We also specialize in preparing software solutions for integrating systems, making it easy to manage and analyze data from multiple sources. We work with all kinds of data architectures used for collecting, managing, storing, and processing large volumes of data from various sources, providing valuable insights into their operations, customers, and markets.

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Data processing
Data processing

At TechMagic, we extract and refine structured and unstructured data from streaming and batch sources, enabling seamless integration with legacy databases or cloud systems. Our team uses advanced techniques to cleanse and transform the data, ensuring its quality and consistency for downstream processing.

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Big data engineering
Big data engineering

TechMagic provides scalable solutions for managing large volumes of data, enabling enterprises to extract valuable insights and make informed decisions. As for big data engineering services, our team designs and implements data architectures that integrate with existing systems and ensure data security. We leverage different technologies to build reliable and high-performance data pipelines that can handle petabytes of data.

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Cloud data engineering services
Cloud data engineering services

We assess and architects the cloud setup for your business minimizing infrastructure costs and improving business agility. Providing data engineering consulting, we help organizations seamlessly migrate their data to the cloud without risking data quality. Starting with defining a roadmap, strategy, and approach to building and sustaining the most optimal data platform with toolkits, and accelerators.

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Data warehousing
Data warehousing

With data warehousing service, you can store and organize large amounts of data in a structured format, making it easy to access, analyze, and report on. Data is stored in a structured format, making it easy to query, report on, and analyze. By centralizing their data in one repository, clients can eliminate data silos, minimize data duplication, and optimize data quality. This, in turn, leads to better data management and improved decision-making capabilities. We leverage the latest tools for data modeling, querying, and analysis to provide our clients with the most effective data warehousing solutions. Our expertise in data engineer consultancy, specifically warehousing and automation tools enables us to create scalable and reliable pipelines that can handle diverse data sources, automate data flows, and enhance query performance.

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Big data storage
Big data storage

We implement big data infrastructures that leverage and extend their current IT infrastructure or build new ones. Among the best data engineering companies, we have experience in extracting, processing, transforming, and loading data into various relational, non-relational, NoSQL, big data systems, and cloud storage. Depending on the data's availability, volume, velocity, and type, we choose the appropriate storage solution that meets our client's needs. With our solutions, you can store and access vast amounts of data in an efficient and cost-effective manner, scaling up and down quickly as your business grows.

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Data migration
Data migration

Our data migration services provide a streamlined process for migrating business data from on-premises legacy systems to cloud storage infrastructure or new target platforms. We enable you to seamlessly transition your data to its new storage. Our data engineering team builds production-grade, repeatable, and independent data workflow pipelines to move, transform, and store data. We use a range of legacy, Big Data, cloud orchestration and data management pipeline tools and techniques to process data in batch and real-time, ensuring business continuity and minimizing downtime.

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Data visualization
Data visualization

We transform complex data sets into interactive visual representations. Our team can create custom dashboards and reports that provide actionable insights. This service involves combining data from different sources into a single, unified view. Data visualizations help you to quickly identify patterns, trends, and anomalies in your data, making it easier for you to make informed decisions. We also have expertise in building customized data pipelines that can handle a wide variety of data types, including structured and unstructured data, and can integrate data from cloud-based as well as on-premise sources.

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Data modeling
Data modeling

Our data modeling services involve designing and implementing data structures. Providing data engineering as a service, we take into account your specific requirements, data sources, and data types to create an optimized schema that enables efficient data processing and analysis. We ensure data integrity and consistency through rigorous testing and validation, and continuously monitor and adjust the schema to accommodate evolving business needs.

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Industry recognition
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Building AI-powered recruitment assistant

Learn how we leverage prompt engineering to streamline recruitment processes with AI.

Case study
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Creating intelligent platform to scale eCommerce ROI

Check how we helped Acorn-i to develop a full-serverless Node.js app on AWS for heavy data analytics.

Case study
01

Building AI-powered recruitment assistant

Learn how we leverage prompt engineering to streamline recruitment processes with AI.

Case study
02

Creating intelligent platform to scale eCommerce ROI

Check how we helped Acorn-i to develop a full-serverless Node.js app on AWS for heavy data analytics.

Case study
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Benefits of data engineering with Python
Benefits of data 
engineering with Python
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Custom business logic

Python's simplicity makes it a great choice for writing custom business logic that executes as part of a data pipeline or data transformation and can be integrated seamlessly into your data workflows.

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Improved operational efficiency

Python's simplicity, readability, and ease of use make it an efficient language for data engineering. Its extensive ecosystem and library of pre-built modules and tools enable faster development. Using Python for data engineering, data engineering consulting firms can help businesses extract insights from their data, enabling them to make informed decisions that improve performance and profitability.

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Improved product quality

By analyzing gathered data, you can gain insights into how your products are used and how to improve the user experience. TechMagic uses Python to analyze data and offer solutions on how to improve your product quality or user experience.

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Data-driven insights

Python's machine-learning capabilities can help you predict behaviors based on historical data and identify new business opportunities. With an analytics model for business users and analysts, businesses can make data-driven decisions to identify new opportunities for growth and better serve their customers.

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Automation

Python can be easily integrated with other languages and technologies, making it a versatile tool for building data pipelines and processing large volumes of data. We automate your data workflows and build a data infrastructure that is easy to operate and maintain. Our team can help you monitor and log your data workflows.

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Enhanced compliance

By integrating regulatory and market data, businesses can ensure compliance and align sales and distribution. This not only helps to avoid potential legal issues but also provides transparency in the supply chain.

Benefits of data 
engineering with Python

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Data engineering technologies we use

Amazon
AWS
Amazon AWS
Python
Python
Snowflake
Snowflake
MongoDB
MongoDB
BigQuery
BigQuery
Amazon
Redshift
Amazon Redshift
Apache
Spark
Apache Spark
Airflow
Airflow
Hadoop
Hadoop
Kafka
Kafka
AWS Athena
AWS Athena
AWS Glue
AWS Glue
Why TechMagic
End-to-end data engineering services
End-to-end data engineering services

As a data engineering company, we offer end-to-end data engineering services to clients from different industries. Our services cover the entire data lifecycle, from the discovery phase through implementation and maintenance services. Our data engineering experts have experience working with various data architectures and platforms, such as AWS, Azure, etc.

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Compliance
Compliance

At TechMagic, we follow strict data protection and security standards to ensure that our client's data is always protected. Hire data engineer to work closely and ensure that their data is handled in a compliant and secure manner.

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Experienced specialists
Experienced specialists

Our team is composed of experienced specialists with a deep understanding of data engineering, cloud computing, and AI. Among data engineering companies, we have worked with various clients from different industries, which allows us to develop the expertise needed to solve complex data engineering challenges.

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FAQs
How do you ensure the quality of data engineering services?

At TechMagic, we prioritize quality in everything we do, and our data engineering services are no exception. Our team follows best practices in data quality management, such as data profiling, data cleansing, and data validation, to ensure that the data we process is accurate, consistent, and complete. We also implement rigorous security measures to protect our clients' data, such as access controls and encryption.

What is TechMagic's pricing model for data engineering services?

At TechMagic, we offer flexible pricing models for our data engineering services. We offer both fixed-price pricing models with detailed estimates of the total cost based on the project scope and requirements. This pricing model is best suited for well-defined projects with clear deliverables and timelines.

How is Python used in data engineering? Why it so popular?

Python is a popular programming language used in data engineering for tasks such as data acquisition, data wrangling, data cleaning, and data transformation. Python has a wealth of libraries and tools that make it easy to work with data and create powerful data pipelines and applications.

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Ross Kurhanskyilinkedin
Ross Kurhanskyi
VP of business development