Big Data Engineer

Vintti is a staffing agency with a unique mission: to create win-win scenarios for both US businesses and Latin American professionals. We address the challenges faced by SMBs, startups, and firms in finding the right talent, as well as the aspirations of skilled Latin American workers seeking international opportunities. By bridging this gap, Vintti enables US companies to access a wealth of untapped talent, while providing Latin American professionals with pathways to expand their careers on a global scale. Our approach cultivates a symbiotic ecosystem that benefits all parties involved.

A Big Data Engineer plays a crucial role in harnessing the power of extensive data sets to drive business insights and innovation. Specializing in the design, development, and management of scalable data processing systems, they enable the transformation of raw data into structured, analyzable formats. Utilizing various big data technologies and frameworks, Big Data Engineers collaborate with data scientists, analysts, and other stakeholders to ensure efficient, reliable data flow and accessibility. Their expertise is vital in optimizing data architecture and ensuring seamless integration across diverse data sources, ultimately empowering data-informed decision-making.

- Bachelor’s degree in Computer Science, Information Technology, or a related field.
- Proven experience as a Big Data Engineer or similar role.
- Proficiency in programming languages such as Python, Java, and Scala.
- Extensive experience with big data tools and frameworks, including Apache Kafka, Spark, and Hadoop.
- Strong knowledge of data processing, architecture design, and storage solutions.
- Experience in implementing and managing data lakes and databases.
- Solid understanding of ETL (Extract, Transform, Load) processes and tools.
- Hands-on experience with data validation frameworks and monitoring systems.
- Ability to optimize data processing jobs and troubleshoot issues.
- Knowledge of data security practices and data governance policies.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud.
- Familiarity with containerization and orchestration tools like Docker and Kubernetes.
- Strong problem-solving and analytical skills.
- Excellent collaboration and communication skills.
- Up-to-date with the latest big data technologies and methodologies.
- Ability to work in a fast-paced, dynamic environment.
- Strong attention to detail and commitment to delivering high-quality work.
- Experience with SQL and NoSQL databases.
- Understanding of data warehousing and data modeling principles.
- Ability to automate repetitive tasks using scripting languages or automation tools.
- Experience with performance tuning, troubleshooting, and debugging of big data applications.
- Familiarity with version control systems like Git.
- Ability to document data processing systems and solutions thoroughly.

- Design, implement, and manage large-scale data processing systems.
- Develop, construct, test, and maintain architectures such as databases and large-scale data processing systems.
- Use programming languages such as Python, Java, and Scala to process and analyze large datasets.
- Implement data ingestion pipelines using tools like Apache Kafka, Spark, and Hadoop.
- Create and optimize data storage solutions, including data lakes and databases.
- Ensure data quality and integrity by implementing data validation frameworks and monitoring systems.
- Collaborate with data scientists and analysts to understand data requirements and translate them into efficient data processing solutions.
- Monitor and troubleshoot data processing jobs to ensure they run smoothly and resolve any issues that arise.
- Optimize the performance of big data solutions by tuning hardware and software configurations.
- Implement data security practices to protect sensitive data and ensure compliance with data governance policies.
- Design and maintain ETL (Extract, Transform, Load) processes to streamline data flows.
- Document data processing systems and solutions to facilitate maintenance and future development.
- Conduct research and stay up to date with the latest big data technologies and methodologies.
- Participate in code reviews to ensure high-quality code and adherence to best practices.
- Provide support and consultation for other teams regarding data management best practices.
- Perform data migration tasks as needed to transition data between different systems and platforms.
- Automate repetitive tasks to improve the efficiency and reliability of data processing pipelines.
- Engage in performance tuning, troubleshooting, and debugging of big data applications.
- Collaborate with IT and cloud infrastructure teams to deploy and manage scalable solutions.
- Prepare and deliver progress reports, presentations, and documentation for stakeholders.

The ideal candidate for the Big Data Engineer role will possess a bachelor's degree in Computer Science, Information Technology, or a related field, with substantial experience in similar positions. They will exhibit a deep proficiency in programming languages such as Python, Java, and Scala, alongside extensive experience with big data tools and frameworks, including Apache Kafka, Spark, and Hadoop. With a robust understanding of data processing, architecture design, and storage solutions, they will have a proven track record in implementing and managing data lakes and databases. The candidate will be adept in ETL processes, data validation, and monitoring systems, ensuring data quality and integrity. Their problem-solving and analytical skills will be exceptional, alongside a meticulous attention to detail and a commitment to high-quality work. Demonstrating strong collaboration and communication skills, they will effectively translate data requirements into efficient solutions while simultaneously managing and prioritizing multiple tasks. A proactive, self-motivated attitude, coupled with an ability to quickly adapt to dynamic environments, will be evident. The candidate will stay abreast of the latest technologies and methodologies, showing an innovative mindset and enthusiasm for continuous improvement and automation. Additionally, they will possess experience with cloud platforms, containerization tools, performance tuning, and have a firm grasp of data security practices. Their cooperative team spirit, high integrity, and customer-focused approach will ensure they meet stakeholder needs. Lastly, they will have strong documentation skills, ensuring all data processing systems and solutions are thoroughly documented and easily maintainable.

- Design, implement, and manage large-scale data processing systems.
- Develop, construct, test, and maintain architectures such as databases and large-scale data processing systems.
- Use programming languages such as Python, Java, and Scala to process and analyze large datasets.
- Implement data ingestion pipelines using tools like Apache Kafka, Spark, and Hadoop.
- Create and optimize data storage solutions, including data lakes and databases.
- Ensure data quality and integrity by implementing data validation frameworks and monitoring systems.
- Collaborate with data scientists and analysts to understand data requirements and translate them into efficient data processing solutions.
- Monitor and troubleshoot data processing jobs to ensure they run smoothly and resolve any issues that arise.
- Optimize the performance of big data solutions by tuning hardware and software configurations.
- Implement data security practices to protect sensitive data and ensure compliance with data governance policies.
- Design and maintain ETL (Extract, Transform, Load) processes to streamline data flows.
- Document data processing systems and solutions to facilitate maintenance and future development.
- Conduct research and stay up to date with the latest big data technologies and methodologies.
- Participate in code reviews to ensure high-quality code and adherence to best practices.
- Provide support and consultation for other teams regarding data management best practices.
- Perform data migration tasks as needed to transition data between different systems and platforms.
- Automate repetitive tasks to improve the efficiency and reliability of data processing pipelines.
- Engage in performance tuning, troubleshooting, and debugging of big data applications.
- Collaborate with IT and cloud infrastructure teams to deploy and manage scalable solutions.
- Prepare and deliver progress reports, presentations, and documentation for stakeholders.

- Strong analytical and problem-solving skills
- High attention to detail
- Ability to manage and prioritize multiple tasks
- Excellent communication and collaboration abilities
- Proactive and self-motivated
- Adaptable to fast-paced and dynamic environments
- Strong commitment to delivering high-quality work
- Quick learner with a passion for continuous improvement
- Highly organized with effective time management skills
- Strong team player with a cooperative attitude
- Innovative mindset to approach and solve complex problems
- Ability to work independently and take initiative
- Resilient and able to troubleshoot and resolve issues efficiently
- Persistent in staying up-to-date with the latest technologies and best practices
- Customer-focused with a commitment to understanding and meeting stakeholder needs
- High integrity and dedication to maintaining data security and compliance
- Strong written and verbal communication skills for creating clear documentation and delivering presentations
- Technical proficiency and a deep understanding of big data technologies and methodologies
- Enthusiasm for automation and improving efficiencies in data processing workflows
- Creative thinker with the ability to bring new ideas and approaches to the role

- Competitive salary range based on experience and skills
- Comprehensive health benefits, including medical, dental, and vision insurance
- Retirement savings plan with company matching contributions
- Paid time off, including vacation, sick leave, and holidays
- Flexible working hours and remote work options
- Work-life balance initiatives, such as wellness programs and employee assistance programs
- Opportunities for professional development and continuous learning
- Reimbursement for educational courses, certifications, and training programs
- Access to cutting-edge technology and tools
- Collaborative and inclusive company culture
- Stock options or equity participation plans
- Performance-based bonuses and incentives
- Company-sponsored events and team-building activities
- Generous parental leave policies and family support programs
- State-of-the-art office facilities with ergonomic workspaces
- Access to employee resource groups and diversity initiatives
- Career advancement opportunities with clear growth paths
- Subsidized gym memberships or on-site fitness facilities
- Commuter benefits and transportation subsidies
- On-site or virtual mental health support and resources