Data Engineer (Streaming)

Vintti is a cutting-edge staffing agency revolutionizing the way US companies build their teams. Leveraging advanced technology and embracing the power of remote work, we connect SMBs, startups, and firms across the United States with top-tier talent from Latin America. Our platform seamlessly integrates professionals into US business ecosystems, regardless of physical borders. Vintti operates on the principle of a borderless future of work, where skills and expertise trump geographical constraints.

A Data Engineer (Streaming) focuses on designing, implementing, and maintaining data pipelines that process real-time data streams. They work with technologies such as Apache Kafka, Apache Flink, or similar tools to ensure that data flows seamlessly from source to destination, enabling timely analytics and decision-making. Their responsibilities include building scalable systems for data ingest, processing, and storage, while ensuring data quality and integrity. This role requires a solid understanding of both data architecture and coding skills, as well as a collaborative mindset to work closely with data scientists, analysts, and other stakeholders.

- Bachelor's degree in Computer Science, Engineering, or a related field.
- 3+ years of experience in data engineering, with a focus on real-time data streaming.
- Proficiency in programming languages such as Python, Java, or Scala.
- Strong knowledge of data streaming technologies such as Apache Kafka, Apache Flink, or AWS Kinesis.
- Experience with cloud platforms like AWS, Google Cloud, or Azure.
- Expertise in SQL and experience with relational and NoSQL databases.
- Hands-on experience with data storage solutions, including data lakes.
- Familiarity with big data technologies like Hadoop, Spark, or similar.
- Knowledge of ETL concepts and data pipeline design.
- Experience in data validation, cleansing, and ensuring data quality.
- Understanding of CI/CD workflows and integration with data pipelines.
- Strong problem-solving and troubleshooting skills.
- Excellent communication and collaboration abilities.
- Familiarity with containerization tools like Docker and orchestration tools like Kubernetes.
- Ability to manage multiple tasks and projects in a fast-paced environment.
- Experience with monitoring and logging tools for data pipelines.
- Knowledge of data security and privacy best practices.
- Understanding of agile methodologies and project management tools.

- Design and develop real-time data ingestion and processing pipelines.
- Implement, configure, and maintain data streaming frameworks like Apache Kafka, Apache Flink, or AWS Kinesis.
- Monitor and troubleshoot data pipeline performance issues.
- Write and optimize SQL queries for analytical and business use cases.
- Deploy, manage, and optimize data storage systems including databases and data lakes.
- Automate data collection processes from various sources.
- Ensure data quality through validation and cleansing mechanisms.
- Optimize data flow for performance and scalability improvements.
- Integrate data pipelines into CI/CD workflows with DevOps teams.
- Maintain the health and performance of data stream processing applications.
- Develop and maintain comprehensive documentation of data processing and pipeline architecture.
- Stay updated with the latest technologies and trends in data engineering and streaming.
- Conduct code reviews to ensure adherence to best practices.
- Collaborate with data scientists, analysts, and cross-functional teams to meet project goals.

The ideal candidate for our Data Engineer (Streaming) role holds a Bachelor's degree in Computer Science, Engineering, or a related field, with over three years of experience focused on real-time data streaming. They are proficient in programming languages such as Python, Java, or Scala, and possess strong expertise in data streaming technologies like Apache Kafka, Apache Flink, or AWS Kinesis. Their experience includes working with cloud platforms such as AWS, Google Cloud, or Azure, and they demonstrate excellence in SQL and handling both relational and NoSQL databases. This candidate has a hands-on approach to data storage solutions, including data lakes, and is familiar with big data technologies like Hadoop and Spark. They understand ETL concepts, data pipeline design, and are experienced in data validation and cleansing to ensure data quality. With a clear grasp of CI/CD workflows, they expertly integrate data pipelines and are well-versed in using Docker and Kubernetes for containerization and orchestration. This individual has a strong analytical and problem-solving mindset, excellent communication and collaborative skills, and is adept at managing multiple tasks in a fast-paced environment. They exhibit high ethical standards, a commitment to data privacy and security, and are always eager to stay updated with the latest industry trends. Above all, they are a highly motivated and proactive team player with a strong technical aptitude, consistently delivering high-quality results through innovative solutions while maintaining resilience under pressure.

- Design and develop data pipelines for real-time data ingestion and processing.
- Collaborate with data scientists and analysts to understand data requirements and deliver appropriate solutions.
- Implement and maintain data streaming frameworks such as Apache Kafka, Apache Flink, or AWS Kinesis.
- Monitor data pipeline performance and troubleshoot issues to ensure seamless data flow.
- Write efficient and optimized SQL queries for analytical use cases.
- Deploy and manage data storage systems, including databases and data lakes.
- Automate data collection processes to streamline the ingestion of data from multiple sources.
- Ensure data quality and integrity by implementing validation and cleansing mechanisms.
- Optimize data flow and storage for improved performance and scalability.
- Work with DevOps teams to integrate data pipelines into CI/CD workflows.
- Manage and maintain the health and performance of data stream processing applications.
- Develop and maintain documentation for data processing and pipeline architecture.
- Stay updated with emerging technologies and methodologies in data engineering and streaming.
- Conduct code reviews and provide feedback to ensure best practices are followed.
- Collaborate with cross-functional teams to drive data engineering projects from conception to completion.

- Analytical mindset with strong problem-solving abilities
- Highly motivated and proactive with a passion for data engineering
- Strong attention to detail and commitment to data quality
- Excellent communication and interpersonal skills
- Ability to work both independently and collaboratively in a team
- Strong organizational and time-management skills
- Adaptable and able to learn new technologies quickly
- Creative thinker with a penchant for innovative solutions
- High ethical standards and commitment to data privacy and security
- Ability to handle multiple tasks and prioritize effectively
- Strong decision-making capabilities
- Resilient and able to perform under pressure
- Commitment to continuous improvement and staying updated with industry trends
- Focus on delivering high-quality results
- Strong technical aptitude and hands-on approach to problem-solving

- Competitive salary range of $95,000 - $130,000 per year.
- Comprehensive health, dental, and vision insurance plans.
- 401(k) plan with company match.
- Generous paid time off (PTO) and holidays.
- Flexible work hours and remote work options.
- Professional development and continuous learning opportunities.
- Tuition reimbursement for relevant courses and certifications.
- Wellness programs, including gym membership discounts and mental health resources.
- Collaborative and inclusive company culture.
- Employee stock purchase plan (ESPP).
- Paid parental leave and family support programs.
- Commuter benefits or transportation allowance.
- Access to state-of-the-art technology and tools.
- Regular team-building activities and social events.
- Life and disability insurance coverage.
- Employee recognition and rewards programs.
- Opportunity to work on cutting-edge technologies and innovative projects.