API/Data Engineers

Hire API/Data Engineers

The decisions made throughout the planning and implementation stages have a major impact on a company’s operations. One of the most critical, difficult, and high-stakes choices that a corporation has to make is how to interact with third-party solutions. An Application Program Interface (API) enables organisations to access data from other applications and, when appropriately designed, makes it easy for partners to integrate into their platform. However, an open API may be used by competitors, thus providing new possibilities while still upholding the necessary secrecy within corporate teams. Data Engineering is the process of developing and constructing large-scale data collection, storage, and analysis systems, with applications in almost every sector. Organisations may accumulate vast amounts of data, but they must have the right people and technology in place to guarantee that the data is made available to data scientists and analysts in a usable format. Data engineers create systems that collect, analyse, and convert raw data into information that data scientists and business analysts can use in a variety of scenarios. The ultimate goal is to improve data accessibility so that companies can assess and optimise their performance.

What does API/Data Engineering entail?

APIs are becoming increasingly important in the digital age, as they allow for the efficient management of existing tools as well as the development of new ones. This has led to a heightened demand for API developers and API developer jobs in the tech industry. Consequently, API testing is gaining more attention, as it is essential for the creation of many of today’s popular internet applications. To ensure successful API implementation, having the right automation testing approach, tool, and solution in place is critical. This has resulted in a surge of API developer positions, as businesses are increasingly turning to Big Data for meaningful insights. As a result, data engineers who can handle large amounts of complex data are in high demand, with API/data engineers being some of the most sought-after roles in the business, often receiving generous compensation for their work.

What are an API/Data engineer’s tasks and responsibilities?

An API Developer is an essential part of achieving an organisation’s API-related objectives. As every organisation needs an API Developer, there is always at least one job opportunity available. Their primary role is to understand the API vision defined by the organisation’s stakeholders and collaborate with them to develop an API that meets their specific needs. API Developers employ an API-first design approach to ensure the API provides the best possible design and user experience. Preconceived assumptions should be set aside to facilitate the development and implementation of the API. An API/Data Engineer has the major responsibility of constructing and building a robust infrastructure for transforming data into forms that Data Scientists can interpret. Data Engineers must be able to identify patterns in large datasets and design scalable solutions for converting semi-structured and unstructured data into useful representations. Essentially, Data Engineers prepare and process raw data so that it can be utilised for either analytical or operational purposes. The following are the major duties of an API/Data Engineer:

• Architectures must be created, constructed, tested, and maintained.
• Putting together vast, complicated datasets that are relevant to business requirements
• Use advanced analytics tools, machine learning, and statistical methodologies.
• Methods for modern data security and governance security
• Intricate designs are required to translate complex functional and technical requirements.
• Data storage using Hadoop, NoSQL, and other technologies
• Identifying hidden patterns in data chunks and developing models
• Data management strategies are being integrated into the current organisational framework.
• Assist in the creation of a solid infrastructure and seamless third-party integration.
• Create scalable, high-performance web services for data tracking.
• Analyse, design, develop, code, and implement programs in many programming languages for feature-rich Web Applications.
• Contribute to system integration, testing strategy, scripting, and application debugging.
• Examines the functionality and performance of software programs and databases.
• Produce new programs, modify existing programs, gather test data, and create functional specifications based on the standards.
• Analyse the performance of programs and applications using different programming languages, tools, and methodologies.
• Educate non-technical individuals on how to effectively utilise software and hardware solutions.
• Examine project ideas, assess alternatives, calculate expenses, and provide recommendations.
• System designs and specifications must be developed.
• Identify potential process improvement opportunities, provide alternatives, and give suggestions.

How does one go about becoming an API/Data engineer?

In order to pursue a career in API development, it is important to understand the stages involved in searching for and obtaining an API/Data engineer position. With the rising demand for such roles, there are always openings in well-respected businesses. It should be noted that while a bachelor’s degree is typically required to apply for such roles, no formal education is necessary to become an API/Data engineer. Whether you are a graduate or non-graduate, experienced or inexperienced in the field, you may study API development and make a successful career out of it. When applying for API/Data engineer positions, employers often value applicants with real-world experience in programming and app development. Experience in API testing, cloud protocols and data management/query is also beneficial and can give you an edge over other applicants. Overall, with the proper education, experience and dedication, you can make a successful career in the field of API development.

Qualifications for becoming an API/Data engineer

API/Data engineers need to possess a specialised set of skills that enable them to effectively meet the requirements of their organisation through creating outstanding APIs. It is essential for students seeking to secure high-paying jobs in the field of API/Data engineering to have a comprehensive understanding of these skills.

1. API development

   Having a comprehensive understanding of how to integrate Application Programming Interfaces (APIs) across different systems can help to expand and refine your API knowledge. Learning the API design concepts for each system can be beneficial to mobile and desktop application developers, as it can provide them with the capability to increase their skills and diversity their portfolio. API designers can utilise this knowledge to develop integrated tools, micro-servers that are compatible with multiple platforms, and applications that improve connectivity and team collaboration. For example, a software developer may use API design to bridge the gap between smartphone operating systems and automotive media applications, allowing users to make calls, send and receive text messages, and change music while driving safely.

2. Front-end creation

   Although API development is not typically part of a front-end development curriculum, gaining an understanding of the fundamentals of API development by building applications from scratch can be extremely beneficial. In addition, modern programming standards emphasise the importance of product compatibility throughout the front-end development process. Therefore, front-end developers can use their existing knowledge of program compatibility concepts to expedite the process of learning API development. For example, designing applications for mobile and desktop platforms does not always guarantee API compatibility; however, understanding how to construct software compatibility will help developers quickly adjust to API development.

3. Hadoop and Spark

   The Apache Hadoop software library is a framework designed to facilitate the distributed processing of large data sets across clusters of computers. Utilising basic programming concepts, the framework is capable of scaling from a single server to thousands of computers, each of which contains its own Central Processing Unit (CPU) and storage capacity. Programming languages that are compatible with the framework include Python, Scala, Java, and R. While Hadoop is an incredibly powerful tool for handling vast amounts of data, it is not without its drawbacks, such as slower processing speeds and a much higher requirement for coding. Apache Spark is an alternate data processing engine that allows for continuous input and output of data through stream processing. It shares many of the same functionalities as Hadoop and can be used as an alternative solution when dealing with large volumes of data.

4. Data warehouse

   A data warehouse is a relational database which can be queried and analysed, and is designed to provide a long-term perspective on data with regard to temporal trends. By contrast, a database is typically updated with the most current information. As a result, data engineers must be knowledgeable in the most widely used data warehousing systems, such as Amazon Web Services and Amazon Redshift. Furthermore, most job postings for data engineers include a requirement for experience with AWS.

5. APIs for data

   An Application Programming Interface (API) is a data access interface that enables two applications or devices to interact with one another in order to complete a task. In web applications, APIs are used to facilitate communication between the front-end user interface and the back-end functionality and data. By using an API, an application can access a database, retrieve information from specific database tables, process the request, and return an HTTP-based response which is then displayed in the web browser. APIs are created by data engineers to facilitate querying of databases by data scientists and business intelligence analysts.

How can I acquire a job as a remote API/Data engineer?

At our meeting, we discussed the necessary skills to become a successful API/Data engineer. However, it is essential to remember that continual practice is key to staying up to date with industry advancements. As the career path becomes more popular, competition will become increasingly fierce. To ensure success, it is important to stay informed of the latest trends in the field. Work provides an array of remote API/Data engineer jobs to help you reach your career goals. Through these positions, you will be able to improve your skills by collaborating with other experienced developers to solve complex technical issues. Additionally, by joining a network of the world’s top API/Data engineers, you will have access to full-time, long-term remote API/Data engineer jobs with more desirable pay and greater advancement opportunities.

Job Description

Responsibilities at work

• Create and manage scalable data pipelines, as well as new API connectors.
• Participate in technical conversations to determine techniques and tools for specific projects.
• Implement data quality monitoring methods and procedures.
• Perform the necessary data analysis to troubleshoot data-related problems.
• The goal of this project is to develop the necessary infrastructure to facilitate the connection of large-scale systems for data access and processing. Additionally, we will create Application Programming Interfaces (APIs) that will provide swift and uncomplicated data identification, exploration, and action.
• Visualise abstractions in order to connect disparate data models and systems.

Requirements

• Engineering or computer science bachelor’s/ master’s degree (or equivalent experience)
• At least three years of API development expertise is required (rare exceptions for highly skilled developers)
• Extensive knowledge of Python, R, and API functionality
• Strong SQL, T-SQL, and data manipulation skills are required.
• Data processing experience in Python or Java
• Excellent understanding of RESTful APIs and data streaming
• Knowledge of big data technologies such as Hadoop, Hive, and others.
• capable of creating backend microservices
• Practical knowledge with RDBMS systems (Postgres, MySQL, Oracle, etc.)
• Experience designing large-scale distributed systems
• Knowledge of data structures, distributed systems, concurrency, and threading is essential.
• Working knowledge of Scala, Java, or any JVM-based language
• I’m obsessed with creating interoperable APIs for search, discovery, access, and attribution.
• English fluency is required for good communication.
• Work full-time (40 hours per week) with a 4-hour overlap with US time zones

Preferred skills

• Understanding of web application development (Angular, React)
• Knowledge of event-driven services such as Kafka and Kinesis
• Consider using gRPC to build services.
• A systematic method to unit and integration testing
• Working knowledge of an Agile setting
• Excellent analytical, consultative, and communication abilities
• Outstanding organisational and leadership abilities