Apache Airflow Developers

Hire Apache Airflow Developers

Apache Airflow is an open-source workflow writing and execution platform. It offers a fully automated system for modeling, scheduling, and monitoring activities.

It was created to alleviate the problems that computer programmers had while dealing with long-term “cron” chores and large applications. However, it has since evolved to become one of the most popular software platforms on the market.

Airflow is a data analytics workflow design, scheduling, and monitoring software. A workflow is any series of actions performed to attain a goal. Airflow may be used to operate a sophisticated data pipeline in which linked operations are done in the proper sequence.

What does Apache Airflow development entail?

By combining a number of technologies, Apache Airflow allows users to create complicated workflows for data processing applications. Its Python-based platform provides flexibility and resilience, while its user-friendly interface makes it simple to monitor operations and manage the platform. Because Apache Airflow uses coding to design workflow processes, end users may write their own code that will run at certain phases in a process.

Since its inception as an internal project inside Airbnb, Apache Airflow has gone a long way. Businesses who wish to increase the quality and speed of service/product delivery. They wish to engage Apache Airflow developers to cater to improved operational excellence, a better customer experience, and other strategic goals.

What are an Apache Airflow developer’s duties and responsibilities?

Apache Airflow developers are in charge of completing data loads, optimizing data for extraction and reporting, developing and implementing ETL operations, maintaining complex databases by performing appropriate database administration activities, and so on. Apache Airflow developers monitor, report on, and evaluate use patterns and statistics output to ensure quality control and high performance while retrieving data from a database or other data storage. Furthermore, these programmers provide optimal capacity and application performance.

  • Execute and monitor data loading activities.
  • Optimize data extraction and reporting to improve data extraction and reporting.
  • Large databases may be managed by executing proper database administration operations.
  • Create and distribute ETL jobs
  • Workflows or data pipelines may be created, managed, and configured.
  • Ensure that data retrieval operations run smoothly.

How does one go about becoming an Apache Airflow developer?

Let us now look at how to get a job in the Apache Airflow Development industry. There are no official educational prerequisites to become an Apache Airflow developer. To become an Apache Airflow developer, one must first learn the development of Apache Airflow. You may master the skills required to become an Apache Airflow developer whether you are a graduate or non-graduate, experienced or inexperienced. You can make a career out of it if you have hands-on experience and knowledge in related technical and non-technical abilities.

It is crucial to note, however, that a bachelor’s or master’s degree in computer science or a related area is not required to become a remote Apache Airflow developer. For starters, having a suitable academic background can help you grasp computer programming and web development better. Second, while recruiting Apache Airflow engineers, many companies need applicants to have a certain degree, making it simpler for you to find lucrative job.

Let’s take a look at the abilities and procedures you’ll need to become a successful Apache Airflow developer:

Qualifications for becoming an Apache Airflow developer

Good foundation skills are required to win high-paying Apache Airflow developer jobs. Here’s what you should know.

  1. DBMS

    A database management system (DBMS) is a piece of software or hardware that enables users to create, read, update, delete, and retrieve data from databases. This kind of administration also ensures the data’s security and integrity. A database management system (DBMS) maintains not just the database engine and schema, but also helps to enable concurrency and standard administrative methods.
  2. Hadoop by Apache

    Apache Hadoop is an open-source system for storing and processing huge datasets ranging in size from gigabytes to petabytes. Hadoop connects several computers, enabling them to examine enormous datasets in parallel faster than they could otherwise. As a result, organizations may acquire insights into their data more quickly and effectively.
  3. Database Design

    A database schema is a design for a relational database that may be defined as both visual representations and sets of logical formulae known as integrity constraints. These constraints specify the rules for defining data and manipulating data inside the database. A database schema is part of a database catalog (also known as the information schema in certain databases) and acts as a description of the database’s contents.
  4. SQL 

    Structured Query Language (SQL) is the most widely used database programming language. It is a domain-specific language that may be used to create a database, save data in tables, change, extract, and execute other actions. We are surrounded by data, thus we need a robust database to store it securely, and a language like SQL to administer that database. It has a broad variety of applications and is used to manage and alter data by business executives, developers, and data scientists.
  5. Python

    Python is a popular programming language for web development, data analysis, and artificial intelligence. Python’s easy syntax and readability make it excellent for rapidly developing complicated systems. Furthermore, since Python is cross-platform, object-oriented, and expandable through libraries, it has been extensively accepted for many non-programming applications such as scientific computing, data analysis, and financial management.

Where can I get remote Apache Airflow developer jobs?

Developers are similar to athletes. They must practice efficiently and regularly in order to succeed in their trade. They must also work hard enough so that their talents steadily improve over time. There are two important things that developers must concentrate on in order for that growth to occur: the help of someone more experienced and successful in practice methods when you’re practicing. As a developer, you must know how much to practice, so make sure you have someone to assist you and keep an eye out for indications of burnout!

Works provides the top remote Apache Airflow developer jobs that are tailored to your career goals as an Apache Airflow developer. Grow quickly by working on difficult technical and commercial issues with cutting-edge technology. Join a network of the world’s greatest developers to find full-time, long-term remote Apache Airflow developer jobs with greater pay and opportunities for advancement.

Job Description

Responsibilities at work

  • Execute and supervise data loading activities
  • Enhance data extraction and reporting.
  • Manage large databases by executing appropriate database administration procedures.
  • ETL tasks must be designed and implemented.
  • Create, manage, and coordinate processes or data pipelines.
  • Ensure that data retrieval operations function well.

Requirements

  • Bachelor’s/degree Master’s in computer science or information technology (or equivalent experience)
  • 3+ years of experience as an Apache Airflow developer in the industry (rare exceptions for highly skilled candidates)
  • Expertise in Apache Airflow development
  • Python and its frameworks expertise
  • Knowledge of data warehouse principles and ETL technologies is required (like Informatica, Pentaho, Apache Airflow)
  • Working knowledge of SQL and reporting tools is required (like Power BI and Qlik)
  • English fluency is required for collaboration with engineering management.
  • Work full-time (40 hours a week) with a 4-hour time difference with US time zones.

Preferred skills

  • Knowledge of Apache Hadoop, HDFS, Hive, and other related technologies.
  • Excellent troubleshooting and debugging abilities 
  • Ability to work both solo and in multidisciplinary teams
  • Working understanding of agile processes and methodologies.