Hire Expert Data Engineers

Overcome data challenges with elite data engineering services. Streamline your data processes, improve data quality, optimize data infrastructure, and unlock actionable insights to drive your business forward. Meet your candidates.

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Sphere Partners

Powering Innovations at 350+ Companies Worldwide

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Selected Data Engineers for Your Business

Set up processes to collect, import, and store large amounts of data. Design and implement databases and data processing systems. Create data pipelines that transform, clean, and aggregate data from various sources. Sphere’s engineers are equally adept at developing from scratch as they are at improving existing processes.

All you need to do is choose your next professional, or let us find one for you.

Hasmik
Hasmik Data Analyst
Armine
Armine Data Analyst
Kirill
Kirill Business Analyst
Hasmik
Hasmik Data Analyst
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Experienced Data Analyst and BI Developer with a proven track record of over 6 years in data mining and visualization. She was recognized as a Microsoft-certified Data Science Associate and Data Engineer Associate.

TECHNOLOGIES
Programming Languages/TechnologiesSQLPostgreSQLPythonTableuFrameworksPower BIMethodologiesAzure Data Factory
PROJECT HIGHLIGHTS Integrated client systems and reporting in Power BI for a marketing firm
Implemented a reporting system for a gold mining company using Azure Data Factory and Power BI
Built data architectures with Azure solutions for efficient processing and visualization
Conducted big data analytics to inform strategic decisions
Developed and maintained reporting systems, utilizing tools like QlikView and Power BI
Implemented machine learning algorithms for enhanced data analysis
Conducted web analytics and ML implementation for performance optimization
Developed reporting systems and data visualization using various technologies like Google Analytics, Python, and Tableau
Armine
Armine Data Analyst
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Experienced business intelligence and data analyst with a demonstrated history of working in TechStarted career as a web developer and later on specialized in data and business intelligence sphere

TECHNOLOGIES
Programming Languages/TechnologiesSQLPythonRTableauPower BIGoogle Data StudioSnowflakeAWS RedshiftMicrosoft Power QueryDAXMethodologyData miningAnalytics and VisualisationFrameworkLookerGrafanaTableau Prep Builder
PROJECT HIGHLIGHTS Developed Tableau dashboards and optimized performance, collaborating with team leads
Wrote Python scripts for data manipulation and conducted proof-of-concepts for tool selection
Kirill
Kirill Business Analyst
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Experienced Business Analyst with a demonstrated history of working in the insurance industry. Skilled in Analytical Skills, Operations Management, Product Cost Analysis, Financial Risk, and Organizational Development. Strong information technology professional with a Master of Economics degree focused in Economics and Finances.

TECHNOLOGIES
ToolsUMLSQLMS SQLJiraConfluencePower BITableauExcelSharePointSkills and CompetenciesFinancial analysisAnalysis of current financial indicatorsFinancial control and planningPlan-fact analysis of the budget, budgeting, financial modellingTeam managementBusiness process optimisationStrategic planning
PROJECT HIGHLIGHTS Created and delivered management dashboards and canned reports to support routine management oversight of business processes to ensure critical insight into exceptions and deliverables
Gathered, arranged, and inspected data to deduce information that was used to shape the KPIs of the company
Involved in automation/improvement ETL (Extract, Transform, Load) process for data
Reviewed and analysed customer process and drew it in the flowchart to assist automation/improvement ETL
Performed data profiling to identify and understand anomalies
Used Tableau/Power BI for visualisations

Dedicated Data Services

Focused on scalability, security, and efficiency, our data engineers can rapidly integrate into your project, accelerating your progress towards critical milestones.

Choose the best for your business with our handpicked data engineers. Elevate your data management, ensure smooth operation, and unlock new insights with expert support.

Sphere Partners Try Risk-Free: No upfront commitment
Sphere Partners Quick Start: Developers ready in days
Sphere Partners Adjustable Teams: Scale as needed
Sphere Partners Right Talent, On Time: Dozens on Data Engineers
Sphere Partners Seamless Fit: Integrates with your process
Sphere Partners Agile Experts: Streamlined project management

Sphere’s Strategic Staffing Process

With a successful track record spanning more than 19 years in staff augmentation, we pride ourselves on a straightforward yet effective formula for success: an extensive in-house talent network of over 400 full-time engineering and development professionals worldwide. We utilize a rigorous, multi-step recruitment process held to the highest standards, designed to secure the best talent for your critical projects.

Step 1: Holistic Requirements

Gathering Holistic Requirements

Uncovering the Why in Hiring

It’s not just about needing an ‘X’ developer; it’s about understanding the deeper reasons ‘why’. The journey starts with asking the right questions to ensure a grasp not only of the immediate requirements but also of the broader context and objectives of your project.

This thorough understanding allows us to provide more than just a developer; you receive a staffing solution that aligns perfectly with your unique needs.

Step 2: Initial Interview

Initial Interview and Screening

Comprehensive Candidate Evaluation

All Sphere developers are full-time hires and integral members of our team from the outset. Therefore, the recruitment process extends beyond just assessing technical expertise; it includes evaluating whether the candidates recommended to you can communicate effectively in your company’s language and understand your industry’s specific terminologies.

This approach ensures that you receive professionals who are not only skilled but also meet the strictest standards.

Step 3: Technical Interviews

In-Depth Technical Interviews

Beyond Technical Skills: Total Fit Screening

In our recruiting’s next step of technical interviews, we prioritize matching the talent with your project requirements. Our goal is not to simply check if the candidate knows specific programming languages or technologies; we strive to gauge their comprehensive understanding of the intricacies behind these technologies.

Our technical interviews are conducted with the highest standard—to the point of often leaving applicants even more eager to work with us and be a part of the project.

Step 4: Success Interviews

Client Success Interviews

Ease of Team Integration and Cultural Fit

Each candidate passes extra screening with your assigned client success partners. They conduct cultural fit interviews to ensure that the candidates align well with your team’s culture and product vision.

This step is vital to guarantee that our final recommended candidate not only meets the technical requirements but also embodies the values and ethos of the team behind the project—all essential for a harmonious and productive collaboration.

Step 5+: Continuous Success

Continuous Success Program

Our Partnership Perfection Promise

Every client’s project is unique, so our success team maintains regular communication with your project leaders, implementing a continuous and systematic feedback process.

This ensures that the development resource remains the perfect fit for your needs—whether it’s for 7 days, 30 days, a year and beyond. And, in the rare event that our match does not meet your expectations, we proactively address any issues, including providing an immediate replacement if necessary.

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Engage Leading Data Engineering Talent

Why Sphere?

We validate your business strategy and build a practical, agile, and actionable Data and AI solution, made specifically according to your business needs. We’ve provided Data & Intelligence services for organizations in fintech, e-commerce, healthcare, e-mobility, banking, insurance, and logistics.

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Completed Projects for Startups
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Hear the Stories of Our Clients

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Corporate Knowledge Agent for Financial Services

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Stellar Virtual

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Implementing Customer Analytics for Personalized Banking in a Major Bank

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Data Engineering Frequently Asked Questions

Data Engineering is the practice of designing and building systems for collecting, storing, and analyzing data at scale. It involves the development of architectures and processes that allow for the efficient handling and transformation of large datasets to enable data analysis, reporting, and data-driven decision-making.

A data engineer is responsible for designing, building, and managing the infrastructure and architecture that allow large volumes of data to be processed and analyzed. Here’s what they typically do:

  1. Develop and Construct Data Architecture: They design and implement the databases and data processing systems needed for storing and managing big data. This involves selecting the right database models, coding pipelines, and setting up data warehousing solutions.
  2. Data Collection and Storage: Data engineers set up data ingestion processes to collect, import, and store large amounts of data from various sources. They ensure that data is securely and efficiently stored in a way that makes it accessible for analysis.
  3. Build and Maintain Pipelines: They create data pipelines that transform, clean, and aggregate data from different sources. These pipelines prepare data for analysis by data scientists and other stakeholders.
  4. Ensure Data Quality and Consistency: Data engineers are responsible for maintaining the integrity and reliability of data. They implement measures to detect and correct errors and inconsistencies, ensuring that data is accurate and available for use.
  5. Optimize Data Ecosystem: They work on improving the performance of data processing and storage systems. This involves optimizing SQL queries, ensuring efficient data flow, and implementing best practices for data management.
  6. Collaborate with Data Scientists and Analysts: Data engineers provide the infrastructure and tools needed for data scientists and analysts to carry out their work. They ensure that data is in a usable format and accessible for analytics and business intelligence.

Overall, data engineers play a crucial role in enabling companies to make informed decisions based on large sets of structured and unstructured data. They bridge the gap between the collection of data and its analysis, ensuring that data is not only available but also meaningful and secure.

Data engineering covers a wide range of use cases, including:

  1. Data Warehousing: Building and maintaining repositories for storing and managing large volumes of historical data.
  2. Big Data Processing: Implementing systems to process and analyze large datasets using technologies like Hadoop, Spark, or cloud-based solutions.
  3. Data Pipeline Construction: Designing and implementing pipelines that automate the flow of data from various sources, transforming and cleaning the data as needed.
  4. Real-Time Data Processing: Developing systems that process and analyze data in real-time for applications such as live dashboards, monitoring, and instant decision-making.
  5. Machine Learning Data Pipelines: Preparing and optimizing data for machine learning models, including feature extraction, normalization, and sampling.
  6. Business Intelligence and Analytics: Enabling data-driven decisions by providing clean, structured data for business intelligence tools and analytics platforms.
  7. Data Governance and Compliance: Establishing policies and systems to ensure data quality, security, privacy, and compliance with regulations.
  8. Internet of Things (IoT) Data Management: Managing and analyzing data generated from IoT devices for applications in various industries like manufacturing, healthcare, and smart cities.

Each of these use cases involves specific challenges and requirements, and data engineers play a key role in addressing them to leverage data effectively for business or operational goals.

Sphere’s wide network of top, global engineers are the quickest and easiest way to not only access data talents, but be guaranteed that they can be onboarded seamlessly to your project. It’s crucial to look for developers with experience in your project’s specific technologies and a strong portfolio of successful projects—Sphere helps you do just that.

Find Your Next Data Scientist, Analyst, or Engineer