Data Engineer

Vintti is a staffing agency that leverages the geographical advantage of Latin America to benefit US businesses. We connect companies with professionals who work in time zones closely aligned with or identical to US hours, ensuring seamless communication and collaboration. This synchronicity allows for real-time interaction, enhancing productivity and eliminating the delays often associated with offshore staffing.

A Data Engineer is responsible for designing, constructing, and maintaining the architecture that allows for the collection, processing, and analysis of large volumes of data. Their work ensures that data pipelines are efficient, scalable, and reliable, enabling organizations to make informed decisions. Utilizing tools and technologies for data integration, transformation, and storage, Data Engineers collaborate closely with Data Scientists and Analysts to ensure that data is accessible and actionable. They also focus on optimizing data flows, developing robust data models, and maintaining data integrity and security across various data sources.

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Proven experience as a Data Engineer or in a similar role.
- Strong proficiency in SQL and database management.
- Experience with ETL processes and tools (e.g., Apache NiFi, Talend, Informatica).
- Familiarity with data warehousing solutions such as Redshift, Snowflake, or BigQuery.
- Knowledge of data modeling, schema design, and data architecture principles.
- Experience working with cloud platforms such as AWS, Azure, or Google Cloud.
- Proficiency in programming languages such as Python, Java, or Scala.
- Understanding of distributed systems and big data technologies (e.g., Hadoop, Spark, Kafka).
- Experience with workflow orchestration tools (e.g., Apache Airflow, Luigi).
- Familiarity with data governance and data quality frameworks.
- Strong problem-solving and analytical skills.
- Ability to work collaboratively in a team environment.
- Excellent communication and documentation skills.
- Understanding of data security and compliance requirements (e.g., GDPR, HIPAA).
- Experience with machine learning frameworks and deploying models (e.g., TensorFlow, PyTorch) is a plus.
- Knowledge of version control systems like Git.
- Ability to stay updated with the latest trends and technologies in data engineering.

- Design, develop, and maintain scalable data pipelines and ETL processes.
- Collaborate with data scientists, analysts, and stakeholders to gather requirements and define data solutions.
- Optimize, troubleshoot, and refine data workflows and pipeline issues.
- Build and manage data warehouses and data lakes for analysis and business intelligence.
- Implement data validation and quality assurance checks.
- Monitor and improve the performance of data systems.
- Ensure data security and compliance with industry standards and regulations.
- Automate routine data processing and management tasks.
- Develop and maintain technical documentation for data pipelines and databases.
- Perform data modeling and schema design.
- Work with cloud services and platforms such as AWS, Azure, or Google Cloud.
- Develop and deploy machine learning models and algorithms.
- Integrate data from various internal and external sources.
- Stay current with emerging data technologies and best practices.
- Participate in code reviews and provide feedback to peers.
- Implement data governance policies and practices.
- Support data-related tasks in software development projects.

The ideal candidate for the Data Engineer role is a highly skilled professional with a Bachelor's or Master's degree in Computer Science, Engineering, or a related field, and a proven track record of success in data engineering or similar positions. They possess strong proficiency in SQL and database management, coupled with hands-on experience in designing, developing, and maintaining ETL processes using tools like Apache NiFi, Talend, or Informatica. With a solid understanding of data warehousing solutions such as Redshift, Snowflake, or BigQuery, the candidate is adept at data modeling, schema design, and has a thorough knowledge of data architecture principles. Their technical expertise extends to programming languages like Python, Java, or Scala, and they are well-versed in working with cloud platforms like AWS, Azure, or Google Cloud. The ideal candidate demonstrates familiarity with distributed systems and big data technologies, including Hadoop, Spark, and Kafka, and has experience with workflow orchestration tools such as Apache Airflow or Luigi. They exhibit strong problem-solving and analytical skills, with a keen eye for detail and a commitment to best practices in data governance, security, and compliance. Excellent communication and documentation abilities enable them to collaborate effectively with data scientists, analysts, and other stakeholders, translating requirements into robust data solutions. They are proactive, self-motivated, and exhibit a strong sense of ownership, continually seeking to stay updated with emerging technologies. Their adaptability, innovative mindset, and the ability to perform under pressure while maintaining a commitment to quality and continuous improvement set them apart. With high ethical standards and integrity, they thrive in a collaborative team environment, demonstrating a passion for data and a dedication to driving business intelligence and analytics initiatives forward.

- Design, develop, and maintain scalable data pipelines.
- Extract, transform, and load (ETL) processes for data ingestion.
- Collaborate with data scientists, analysts, and other stakeholders to gather requirements and define data solutions.
- Optimize and troubleshoot data workflows and pipeline issues.
- Build and manage data warehouses/data lakes for analysis and business intelligence.
- Implement data validation and quality assurance checks.
- Monitor the performance of data systems and make recommendations for improvements.
- Ensure data security and compliance with industry standards and regulations.
- Automate routine tasks for data processing and management.
- Develop and maintain technical documentation for data pipelines and databases.
- Perform data modeling and schema design.
- Work with cloud services and platforms such as AWS, Azure, or Google Cloud.
- Develop and deploy machine learning models and algorithms.
- Integrate data from various sources, both internal and external.
- Stay current with emerging data technologies and best practices.
- Participate in code reviews and provide constructive feedback to peers.
- Implement data governance policies and practices.
- Support data-related tasks in software development projects.

- Strong analytical and problem-solving skills
- Excellent communication and interpersonal abilities
- High attention to detail and accuracy
- Strong organizational and time management skills
- Ability to thrive in a collaborative, team-oriented environment
- Eagerness to learn and stay updated with emerging technologies
- Proactive and self-motivated with a strong sense of ownership
- Adaptable and open to feedback
- Innovative and forward-thinking mindset
- Ability to work effectively under pressure and meet deadlines
- Passionate about data and technology
- Strong adherence to best practices and industry standards
- Commitment to quality and continuous improvement
- Strong ethical standards and integrity

- Competitive salary range based on experience and skills
- Comprehensive health insurance (medical, dental, vision) for employees and dependents
- Flexible work hours and remote working options
- Generous paid time off (PTO) and holiday leave
- 401(k) retirement plan with company match
- Stock options or equity participation
- Professional development opportunities and support for certifications
- Access to online learning platforms and training programs
- Employee wellness programs and resources
- Employee assistance programs (EAP)
- Onsite gym or fitness membership reimbursement
- Commuter benefits and travel reimbursement
- Collaborative, inclusive, and innovative work environment
- Opportunities for career advancement and internal mobility
- Regular team-building activities and social events
- Company-sponsored hackathons and tech conferences
- State-of-the-art hardware and software tools for work
- Parental leave and family support programs
- Life and disability insurance plans
- Performance-based bonuses and incentives