Streaming Data Engineer

At Vintti, we specialize in providing US businesses with staffing solutions that feel local. By connecting companies with Latin American professionals operating in compatible time zones, we ensure that work schedules align naturally with US business hours. This temporal harmony facilitates immediate response times, efficient project management, and a cohesive team dynamic regardless of physical location.

A Streaming Data Engineer is responsible for designing, building, and maintaining systems that process real-time data streams. This role involves working with cutting-edge technologies to ensure the seamless flow and transformation of data from various sources to destinations, enabling timely insights and data-driven decisions. Key activities include developing scalable data pipelines, optimizing system performance, and ensuring data integrity and security. A Streaming Data Engineer collaborates closely with data scientists, software developers, and business analysts to support real-time analytics and machine learning applications, making impactful contributions to the organization’s data strategy.

- Bachelor's degree in Computer Science, Engineering, or a related field
- Proven experience as a Data Engineer with a focus on streaming data
- Proficiency with data streaming tools such as Apache Kafka, Apache Flink, and Amazon Kinesis
- Strong programming skills in languages like Java, Scala, Python, or similar
- Experience with data modeling, ETL processes, and data warehousing solutions
- Knowledge of cloud platforms such as AWS, Azure, or Google Cloud
- Familiarity with database technologies (e.g., SQL, NoSQL) and data storage solutions
- Strong understanding of data architecture, data management, and database principles
- Experience with monitoring and logging tools to ensure system reliability
- Solid understanding of data quality, data validation, and data governance practices
- Experience with CI/CD pipelines and DevOps practices for data pipeline deployments
- Ability to troubleshoot and resolve issues in complex data architectures
- Strong analytical and problem-solving skills
- Excellent communication and collaboration skills
- Ability to work in a fast-paced, dynamic environment
- Experience with performance tuning and optimization of large-scale data systems
- Familiarity with containerization tools like Docker and orchestration tools like Kubernetes
- Knowledge of security and privacy best practices in data management
- Ability to conduct performance testing and benchmarking of data systems
- Willingness to stay updated with industry trends and emerging technologies in streaming data engineering

- Design, develop, and maintain real-time data processing pipelines
- Build and optimize data streaming architectures using tools like Apache Kafka, Apache Flink, or Amazon Kinesis
- Monitor streaming data systems to ensure high performance and reliability
- Collaborate with software engineers, data scientists, and other stakeholders to define data requirements and deliver solutions
- Implement data quality checks and validations to ensure data integrity and accuracy
- Develop and maintain ETL processes to transform and analyze streaming data
- Manage and optimize the storage and retrieval of large-scale streaming datasets
- Evaluate and integrate new data sources and technologies to enhance streaming capabilities
- Troubleshoot and resolve technical issues related to streaming data infrastructure and workflows
- Perform capacity planning and scalability assessments to ensure system robustness
- Create and maintain documentation for data pipelines, architecture, and processes
- Continuously improve system performance through monitoring, tuning, and testing
- Provide support for data pipeline deployment and maintenance in production environments
- Analyze and optimize existing streaming data processes for efficiency and cost-effectiveness
- Maintain data security and privacy standards in compliance with organizational policies
- Participate in code reviews and provide constructive feedback to peers
- Automate repetitive tasks and processes to improve overall workflow efficiency
- Collaborate with the DevOps team to implement CI/CD practices for data pipeline deployments
- Stay up-to-date with the latest industry trends and emerging technologies in streaming data engineering
- Conduct regular performance testing and benchmarking of streaming data systems

The ideal candidate for the Streaming Data Engineer role is a highly skilled professional with a Bachelor's degree in Computer Science, Engineering, or a related field, and proven experience in data engineering with a specialization in streaming data. This individual will possess a deep proficiency with data streaming tools such as Apache Kafka, Apache Flink, or Amazon Kinesis, and demonstrate strong programming skills in languages like Java, Scala, Python, or similar. Their expertise will extend to data modeling, ETL processes, data warehousing, and a robust understanding of cloud platforms like AWS, Azure, or Google Cloud. They will have a solid grasp of database technologies (SQL, NoSQL) and data storage solutions, complemented by their knowledge of data architecture principles and governance practices. The ideal candidate will excel in performance tuning and optimization of large-scale data systems and will be adept at using monitoring and logging tools to ensure system reliability. Demonstrating excellent analytical and problem-solving skills, they will seamlessly collaborate with cross-functional teams, bringing strong communication and interpersonal abilities to the table. They will proactively identify and resolve issues in complex data architectures, embrace CI/CD pipelines and DevOps practices, and stay updated with emerging technologies in the field. This candidate will be adaptive, detail-oriented, and highly organized, capable of managing multiple tasks with strategic focus and a commitment to continuous improvement and innovation. Their high ethical standards, customer-focused mindset, and relentless drive for results will make them an invaluable asset to the team.

- Design, develop, and maintain real-time data processing pipelines.
- Build and optimize data streaming architectures using tools like Apache Kafka, Apache Flink, or Amazon Kinesis.
- Monitor streaming data systems to ensure high performance and reliability.
- Collaborate with software engineers, data scientists, and other stakeholders to define data requirements and deliver solutions.
- Implement data quality checks and validations to ensure data integrity and accuracy.
- Develop and maintain ETL processes to transform and analyze streaming data.
- Manage and optimize the storage and retrieval of large-scale streaming datasets.
- Evaluate and integrate new data sources and technologies to enhance streaming capabilities.
- Troubleshoot and resolve technical issues related to streaming data infrastructure and workflows.
- Perform capacity planning and scalability assessments to ensure system robustness.
- Create and maintain documentation for data pipelines, architecture, and processes.
- Continuously improve system performance through monitoring, tuning, and testing.
- Provide support for data pipeline deployment and maintenance in production environments.
- Analyze and optimize existing streaming data processes for efficiency and cost-effectiveness.
- Maintain data security and privacy standards in compliance with organizational policies.
- Participate in code reviews and provide constructive feedback to peers.
- Automate repetitive tasks and processes to improve overall workflow efficiency.
- Collaborate with the DevOps team to implement CI/CD practices for data pipeline deployments.
- Stay up-to-date with the latest industry trends and emerging technologies in streaming data engineering.
- Conduct regular performance testing and benchmarking of streaming data systems.

- Strong attention to detail and accuracy
- Proactive problem solver
- Self-motivated and goal-oriented
- Excellent communication and interpersonal skills
- Collaborative team player
- Innovative and forward-thinking
- Ability to work under pressure and meet deadlines
- Eagerness to learn and adopt new technologies
- Strong analytical reasoning and critical thinking
- High degree of adaptability and flexibility
- Ability to manage multiple tasks and projects simultaneously
- Strong organizational skills
- Proficient in documenting and maintaining detailed records
- Ability to break down complex problems into manageable tasks
- Strategic thinker with a focus on long-term goals
- Commitment to continuous improvement and optimization
- Drive for results and high accountability
- High ethical standards and integrity
- Strong customer-focused mindset

- Competitive salary range based on experience and qualifications
- Comprehensive health, dental, and vision insurance plans
- 401(k) retirement plan with company match
- Paid time off (PTO) and company holidays
- Flexible work hours and remote work options
- Professional development and training opportunities
- Tuition reimbursement for job-related courses and certifications
- Employee wellness programs including gym memberships and wellness incentives
- Paid parental leave and family support programs
- Stock options or equity participation (if applicable)
- Employee assistance programs (EAP) for mental health support
- On-site childcare facilities or childcare assistance programs (if applicable)
- Generous relocation assistance (if applicable)
- Monthly or annual performance bonuses
- Commuter benefits and transportation reimbursement
- Company-sponsored social events and team-building activities
- Access to the latest tools and technologies
- Mentorship and leadership development programs
- Opportunities for career advancement and internal promotions
- A collaborative and inclusive work environment