Apache Spark Developer

Vintti specializes in providing US companies with a financial edge through smart staffing solutions. We bridge the gap between American businesses and Latin American talent, offering access to a vast pool of skilled professionals at competitive rates. This approach enables our clients to scale their operations more efficiently, reduce hiring costs, and invest in growth opportunities without compromising on quality.

An Apache Spark Developer specializes in building and optimizing large-scale data processing applications using Apache Spark. This role involves designing, developing, and deploying data pipelines that perform extract, transform, and load (ETL) operations efficiently on massive datasets. These professionals collaborate with data engineers, data scientists, and other stakeholders to implement scalable solutions that support real-time analytics and machine learning tasks. They possess strong programming skills in languages like Java, Scala, or Python and are adept at leveraging Spark's core components to deliver high-performance, distributed computing capabilities for various data-driven applications.

- Bachelor's degree in Computer Science, Engineering, or a related field.
- Proven experience in developing Apache Spark applications.
- Proficiency in Scala, Python, or Java programming languages.
- Strong understanding of Spark architecture and its components.
- Experience with big data technologies such as Hadoop, Hive, and Kafka.
- Proficient in SQL and data modeling.
- Expertise in designing and implementing ETL pipelines.
- Experience in optimizing Spark applications for performance and scalability.
- Strong analytical skills to analyze large data sets and identify patterns.
- Knowledge of data warehousing concepts and best practices.
- Familiarity with distributed computing principles.
- Experience in version control systems like Git.
- Understanding of data security protocols and best practices.
- Excellent problem-solving and debugging skills.
- Strong communication and collaboration skills.
- Ability to work in an Agile development environment.
- Experience with cloud platforms like AWS, Google Cloud, or Azure is a plus.
- Familiarity with containerization technologies such as Docker and Kubernetes is a plus.
- Strong attention to detail and commitment to producing high-quality work.
- Ability to mentor and train junior developers.

- Develop, test, and implement Apache Spark applications using Scala, Python, or Java.
- Analyze large data sets to identify patterns and trends.
- Optimize Spark applications for performance and scalability.
- Collaborate with data scientists and analysts to understand project requirements.
- Write and maintain robust, scalable, and high-quality code.
- Integrate Spark with other big data technologies such as Hadoop, Hive, and Kafka.
- Monitor and troubleshoot Spark jobs and address any performance issues.
- Implement data processing pipelines for ETL (Extract, Transform, Load) purposes.
- Ensure data integrity and quality through thorough validation and testing.
- Participate in code reviews and contribute to continuous improvement practices.
- Maintain and update technical documentation for Spark applications and processes.
- Collaborate with cross-functional teams to deliver end-to-end data solutions.
- Define and enforce best practices for data processing and storage.
- Stay updated with the latest trends and best practices in big data and Spark.
- Assist in training and mentoring junior developers in Spark and related technologies.
- Implement and manage data security protocols to secure sensitive data.
- Participate in Agile ceremonies like stand-ups, sprint planning, and retrospectives.
- Debug and resolve technical issues related to distributed data processing.
- Provide support and maintenance for existing Spark applications.

The ideal candidate for the Apache Spark Developer role is a highly skilled professional with a Bachelor's degree in Computer Science, Engineering, or a related field, and a proven track record in developing robust and scalable Apache Spark applications using Scala, Python, or Java. This individual possesses a deep understanding of Spark architecture and distributed computing principles, along with hands-on experience in big data technologies such as Hadoop, Hive, and Kafka. They are proficient in SQL, data modeling, and designing ETL pipelines, with a knack for optimizing Spark applications for peak performance. The ideal candidate has strong analytical skills to dissect large data sets, identify patterns, and derive actionable insights. With a solid grasp of data warehousing concepts, data security protocols, and Agile methodology, they are adept at maintaining high-quality code and technical documentation. This person is not only a problem-solver with excellent debugging capabilities but also a collaborative team player who can effectively communicate with cross-functional teams. They are proactive and self-motivated, demonstrating strong attention to detail and a commitment to continuous improvement. An innovative thinker who thrives in a fast-paced, dynamic environment, the candidate possesses outstanding organizational and time management skills. Additionally, their passion for big data technologies and ability to mentor and train junior developers make them a valuable asset to the team. Experience with cloud platforms like AWS, Google Cloud, or Azure, and familiarity with containerization technologies such as Docker and Kubernetes, are considered advantageous.

- Develop, test, and implement Apache Spark applications using Scala, Python, or Java.
- Analyze large data sets to identify patterns and trends.
- Optimize Spark applications for performance and scalability.
- Collaborate with data scientists and analysts to understand project requirements.
- Write and maintain robust, scalable, and high-quality code.
- Integrate Spark with other big data technologies such as Hadoop, Hive, and Kafka.
- Monitor and troubleshoot Spark jobs and address any performance issues.
- Implement data processing pipelines for ETL (Extract, Transform, Load) purposes.
- Ensure data integrity and quality through thorough validation and testing.
- Participate in code reviews and contribute to continuous improvement practices.
- Maintain and update technical documentation for Spark applications and processes.
- Collaborate with cross-functional teams to deliver end-to-end data solutions.
- Define and enforce best practices for data processing and storage.
- Stay updated with the latest trends and best practices in big data and Spark.
- Assist in training and mentoring junior developers in Spark and related technologies.
- Implement and manage data security protocols to secure sensitive data.
- Participate in Agile ceremonies like stand-ups, sprint planning, and retrospectives.
- Debug and resolve technical issues related to distributed data processing.
- Provide support and maintenance for existing Spark applications.

- Strong problem-solving and analytical skills
- Detail-oriented with a commitment to high-quality work
- Strong communication and collaboration abilities
- Ability to work independently and within a team
- Proactive and self-motivated with a willingness to learn
- Adaptable to rapidly changing environments and priorities
- Innovative mindset with the ability to think outside the box
- Strong organizational and time management skills
- Ability to mentor and support junior team members
- Dedicated to continuous improvement and best practices
- Reliable and dependable with a strong work ethic
- Strong technical aptitude and a passion for big data technologies
- Results-driven with a focus on delivering high-impact solutions
- Open to feedback and continuous learning
- Ability to thrive in a fast-paced, dynamic work environment
- Strong interpersonal skills for effective teamwork and collaboration

- Competitive salary range: $100,000 - $150,000 per year
- Comprehensive health, dental, and vision insurance
- 401(k) retirement plan with company match
- Generous paid time off (PTO) and holidays
- Flexible working hours
- Remote work opportunities
- Professional development and training programs
- Tuition reimbursement for continued education
- Opportunities for career advancement and growth
- Employee wellness programs
- Paid parental leave
- Life and disability insurance
- Employee assistance program (EAP)
- Onsite gym or gym membership reimbursement
- Stock options or equity opportunities
- Company-sponsored community service and volunteer events
- Team-building activities and company outings
- Modern and collaborative office environment
- Free snacks and beverages at the office