Latin America has established itself as a hub for technical talent, particularly in data engineering. Professionals here profoundly understand the tools and technologies used in modern data engineering, including SQL, Python, Hadoop, Spark, and cloud services such as AWS and Google Cloud.
Problem solving is one of the most outstanding skills of LATAM Data Engineers, who combine their adaptability and proactive approach to technical and strategic challenges. Their expertise in big data and analytics practices makes them key players capable of driving innovation.
The monthly salary of a data engineer in Latin America varies considerably by country and experience. In Mexico, the average is $2,256; in Colombia, it is $1,100; in Argentina, around $1,072; and in Peru, it is $1,508. Ranges usually oscillate between $600 and $3,700, depending on the level of specialization.
The time difference between some Latin American countries and the US depends on the time zone and daylight saving time. Mexico is aligned with Central Standard Time in the US, while Colombia and Peru are aligned with Eastern Standard Time, although they have a one-hour difference in the summer.
We're committed to clarity in our margins, ensuring they never exceed 20% of the specialist's payment.
At Teilur Talent, we take a mission-focused approach to recruiting, ensuring that our candidates are aligned with your company's vision and goals. Unlike other tech recruiting companies in LATAM, who may focus solely on technical skills, we prioritize the cultural fit and dedication of our team members to your company. For this reason, we do not support project contractor or freelancer roles. Instead, we focus on fully devoted team members who will help you achieve long-term success.
At Teilur Talent, we offer our candidates competitive salaries that are 2x to 3x higher than what tech companies would pay locally. This allows us to attract top talent and retain highly motivated and loyal team members. Additionally, we focus on finding candidates whose values align with the purpose, vision, and mission of our clients. This approach ensures that our engineers and tech talent are not just coding and completing task rather, they become part of a greater purpose, which gives them meaning and helps us attract and retain the best talent.
At Teilur Talent, we specialize in recruiting for a wide range of tech roles that are typically in high demand. These include positions such as DevOps engineers, AI Developers, QA analysts and engineers, back-end and front-end developers, data scientists, product managers, business developers, and technical sales positions. Essentially, we recruit for most roles that are needed in B2B and B2C tech-focused businesses.
At Teilur Talent, we believe in transparency. We charge a flat rate fee of 20% of what the client pays. This way, our clients know exactly what they are paying for and how much the candidate gets. As an example: If a client hires a software engineer for $60,000 per year ($5,000 per month), Teilur's monthly fee would be $1,000 (20% of $5,000). We don't believe in hidden fees or unwanted surprises, so we disclose all costs upfront to both candidates hired and companies. When exploring other alternatives, make sure they are transparent about their pricing. We believe this is paramount for the benefit of all parties involved in this new era of remote work.
At Teilur Talent, we take candidate screening very seriously. We use a multi-layered approach to find the best candidates for our clients, starting with screening thousands of candidates from our internal and proprietary networks. We leverage AI technology to assess whether a candidate matches the technical skills required for a given job opening. We also perform additional personal evaluations to ensure that the candidate has the soft skills, culture fit, and English language skills required to excel in their new role. Our rigorous screening process ensures that only the best candidates make it through to our clients, saving them time and helping them find the best talent for their teams.