Hadoop Developer

Vintti is a staffing agency that acts as an economic enabler. By connecting US-based SMBs, startups, and firms with top-tier Latin American talent, we drive growth on both sides of the equation. For US businesses, we offer access to a pool of highly skilled professionals at competitive rates, allowing for increased efficiency and scalability. For Latin American workers, we provide opportunities to engage with the US market, fostering professional development and economic advancement. Vintti stands at the intersection of global talent and American enterprise, facilitating partnerships that stimulate economic prosperity across borders.

A Hadoop Developer is a specialized software engineer focused on using the Apache Hadoop framework to manage, process, and store large sets of data across distributed systems. They design, develop, and optimize Hadoop-based applications, ensuring efficient data flow and reliable data processing. The role involves working with various Hadoop components such as HDFS, MapReduce, Pig, Hive, and HBase, while also integrating data from different sources. They collaborate with data scientists and analysts to enable meaningful insights from big data, contributing to data-driven decision making and strategic planning within the organization.

- Bachelor’s degree in Computer Science, Information Technology, or a related field.
- Proven experience as a Hadoop Developer or in a similar role.
- Strong understanding of the Hadoop ecosystem and its components, including HDFS, MapReduce, YARN, Oozie, Hive, Pig, Spark, and Flume.
- Proficiency in programming languages such as Java, Python, or Scala.
- Experience with data analytics and data transformation.
- Expertise in writing and optimizing complex MapReduce programs.
- Hands-on experience with Hadoop cluster management and performance tuning.
- Familiarity with big data processing tools and frameworks.
- Strong understanding of data warehousing and ETL processes.
- Knowledge of real-time data streaming and processing tools like Kafka and Storm.
- Excellent problem-solving skills and the ability to troubleshoot and resolve Hadoop cluster issues.
- Ability to develop and document technical designs and coding standards.
- Experience with implementing data quality checks and transformations.
- Understanding of security best practices for Hadoop clusters.
- Ability to manage and maintain Hadoop applications, including performance monitoring and tuning.
- Strong communication and collaboration skills, with the ability to work alongside data scientists, analysts, IT, and operations teams.
- Experience with automating workflows using Oozie.
- Up-to-date with the latest industry trends and emerging technologies related to big data and Hadoop.
- Experience mentoring and guiding junior developers and analysts.
- Strong organizational skills and attention to detail.

- Develop, implement, and maintain Hadoop applications.
- Design scalable data processing frameworks using Hadoop ecosystems and tools like HDFS, MapReduce, YARN, Oozie, Hive, Pig, Spark, and Flume.
- Write and optimize complex MapReduce programs for data analysis.
- Tune Hadoop solutions for performance and scalability.
- Collaborate with data scientists and analysts to process and analyze large datasets.
- Monitor and troubleshoot Hadoop cluster health and resolve performance issues.
- Develop and document technical designs and coding standards.
- Implement data quality checks and transformations.
- Manage and maintain Hadoop applications with ongoing monitoring and tuning.
- Develop and automate workflows using Oozie.
- Integrate Hadoop with other data processing and storage platforms.
- Design data integration solutions.
- Ensure security and compliance best practices for Hadoop clusters.
- Support real-time data streaming and processing solutions.
- Update Hadoop ecosystem components based on industry best practices.
- Develop and maintain technical documentation of processes and systems.
- Mentor and provide guidance to junior developers and analysts.
- Collaborate with IT and operations teams to ensure efficient Hadoop infrastructure operations.
- Stay updated on the latest industry trends and emerging technologies related to big data and Hadoop.

The ideal candidate for the Hadoop Developer role will hold a Bachelor’s degree in Computer Science, Information Technology, or a related field, coupled with substantial proven experience in Hadoop development or a similar role. This individual should demonstrate a deep understanding of the Hadoop ecosystem and its components, including HDFS, MapReduce, YARN, Oozie, Hive, Pig, Spark, and Flume, and possess high-level proficiency in programming languages such as Java, Python, or Scala. With a solid background in data analytics, data transformation, and complex MapReduce program optimization, the ideal candidate will have hands-on experience with Hadoop cluster management and performance tuning, ensuring robust and scalable solutions. A strong knowledge of data warehousing, ETL processes, and real-time data streaming tools such as Kafka and Storm is essential. Excellent problem-solving skills and the ability to troubleshoot and resolve Hadoop cluster issues are required, along with a solid comprehension of security best practices within Hadoop environments. This candidate should excel in developing and documenting technical designs and coding standards, implementing data quality checks, and automating workflows using Oozie. Effective collaboration and communication skills are paramount, as this role involves working closely with data scientists, analysts, IT, and operations teams. A commitment to mentoring junior team members, staying abreast of industry trends and emerging technologies, and possessing strong organizational and time management skills will set the ideal candidate apart. Additionally, the candidate must demonstrate a proactive approach to solving technical challenges, a commitment to continuous learning, the ability to manage multiple tasks and projects simultaneously, and the adaptability to thrive in a dynamic work environment.

- Develop, implement, and maintain Hadoop applications.
- Design and build scalable data processing frameworks using Hadoop ecosystems and tools like HDFS, MapReduce, YARN, Oozie, Hive, Pig, Spark, and Flume.
- Write complex MapReduce programs for data analysis.
- Optimize and tune Hadoop solutions for performance and scalability.
- Collaborate with data scientists and analysts to collect, process, and analyze large datasets.
- Monitor and troubleshoot Hadoop cluster health, including identifying and resolving performance issues and platform operations.
- Develop and document technical designs and coding standards.
- Implement data quality checks and transforms.
- Manage and maintain Hadoop applications by providing ongoing monitoring, tuning, and diagnosing.
- Develop workflows using Oozie and automate tasks for better efficiency.
- Integrate Hadoop with other data processing and storage platforms.
- Participate in designing data integration solutions.
- Ensure security and compliance best practices for Hadoop clusters.
- Provide support for real-time data streaming and processing solutions.
- Update Hadoop ecosystem components in line with industry best practices.
- Develop and maintain technical documentation of processes and systems.
- Provide guidance and mentoring to junior developers and analysts.
- Collaborate with IT and operations teams to ensure the Hadoop infrastructure is operating efficiently.
- Keep abreast of the latest industry trends and emerging technologies related to big data and Hadoop.

- Strong analytical and problem-solving skills
- Excellent attention to detail
- High level of proficiency in programming languages like Java, Python, or Scala
- Deep understanding of the Hadoop ecosystem and related tools
- In-depth experience with data analytics and data transformation processes
- Demonstrated expertise in writing and optimizing MapReduce programs
- Proven ability to manage and tune Hadoop clusters for optimal performance
- Familiarity with data warehousing and ETL processes
- Knowledge of real-time data streaming tools like Kafka and Storm
- Strong documentation and technical writing skills
- Solid comprehension of security best practices within Hadoop environments
- Effective communication and collaboration abilities
- Ability to mentor and guide junior team members
- Adaptability to evolving technologies and industry trends
- Demonstrated organizational and time management skills
- Strong ability to work independently and in a team environment
- Commitment to continuous learning and professional development
- Ability to handle multiple tasks and projects simultaneously
- Proactive approach to identifying and solving technical challenges

- Competitive salary range based on experience and expertise
- Health insurance coverage, including medical, dental, and vision plans
- Retirement savings plan with company matching contributions
- Flexible work hours and remote working options
- Generous paid time off (PTO) and holiday policy
- Professional development and continuous learning opportunities
- Reimbursement for industry certifications and advanced training
- Access to conferences, workshops, and seminars
- Collaborative and inclusive work environment
- Opportunities for career growth and advancement within the company
- Wellbeing programs, including mental health support and gym memberships
- Employee assistance programs (EAP)
- Casual dress code
- Onsite amenities such as a cafeteria and fitness center (if applicable)
- Transportation and commuting subsidies
- Employee referral bonus programs
- Performance-based bonuses and incentives
- Company-sponsored social events and team-building activities
- Access to latest technologies and tools for efficient work
- Support for work-life balance, including family leave policies
- Ergonomic workstations and modern workspaces