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Data Lead at Cresteo. . Location: Remote - Latam. Our Essence:. . Cresteo is on a mission to be the world leader in . people-first. and . honest . nearshore tech services. We prioritize a people-centered approach in an industry that often feels distant and impersonal. Our services are led by experienced, incredibly talented professionals who are changing the system from within - while collaborating with top global clients.. . Our foundation is built on:. . . Deep expertise. . Candid transparency. . Profit-sharing. . Fearless innovation. . . Our team stands out for their deep-rooted passion for corporate change, treating software development as a human sport and art form.. . When it comes to recruitment, we won't box you into rigid questionnaires; we genuinely want to get to know you. Our interactions are not transactional but human-centered, seeking genuine understanding and connection.. . You'll hear about our core values and experience them with us firsthand. They define our essence.. . Join Cresteo and be part of the change we're championing!. Why You Belong Here. . As a Data Engineer at Cresteo, you'll be more than just a developer; you will be part of transforming the tech industry through our honest, transparent, and people-centric approach.. . Your role will be diverse and dynamic. You'll be instrumental in developing and maintaining our software solutions, working with a varied technology stack, and ensuring that our products are functional, efficient, reliable, and scalable.. . By joining us, you're not just choosing a job; you're aligning with a vision that values the human side of tech, where your skills and passion are recognized, nurtured, and celebrated.. . What We're Looking For. . . Extensive experience designing, operating, and evolving production data platforms and modern data warehouse architectures. . Deep hands-on experience with dbt in large-scale production environments, including project structure, model layering, macros, seeds, tests, package management, and dbt Cloud job orchestration. . Proven ability to navigate, troubleshoot, and improve complex dbt projects with hundreds of models and thousands of automated tests. . Strong production experience with Apache Airflow, including DAG design, operators, task groups, sensors, variables, connections, and SLA configuration. . Deep hands-on experience with Amazon Redshift, including schema design, distribution and sort strategies, query performance optimization, and warehouse cost management. . Experience with Redshift Serverless and understanding of RPU usage and consumption-based cost behavior. . Strong dimensional and data warehouse modeling skills, including Slowly Changing Dimensions (SCD Type 2). . Advanced SQL skills, with the ability to understand, troubleshoot, and improve complex existing data models and queries. . Strong Python skills applied to data engineering, ingestion, orchestration, and data processing. . Experience managing data infrastructure through Terraform. . Strong understanding of data quality and automated testing strategies across data pipelines, transformations, and warehouse models. . Ability to build and maintain ingestion processes rather than relying exclusively on managed ELT platforms. . Strong ownership of technical documentation, architecture knowledge, and knowledge-transfer processes, with the ability to progressively absorb and preserve critical platform knowledge. . Experience working within established architectures, with the judgment to understand existing systems before proposing significant changes. . Experience with entity resolution, record matching, master data management, data lineage, or auditability is highly valued. . Experience with AWS Managed Workflows for Apache Airflow (MWAA) is highly valued. . Experience managing cost and performance in consumption-based data warehouse environments is valued. . Experience with regulated, compliance-driven, or high-accountability data environments is valued. . Strong technical leadership, ownership, and decision-making skills, including a clear point of view on data architecture, pipeline reliability, testing, and maintainability. . Professional English communication skills and experience working directly with client stakeholders. . . Lead the evolution of a production data platform built around dbt, Apache Airflow, Amazon Redshift, Python, and AWS, taking ownership of its architecture, reliability, and data quality. Combine hands-on engineering with technical leadership and knowledge transfer to maintain and evolve a complex, business-critical data ecosystem.. Our Commitment to You:. . . 100% Remote. . USD above-average salaries. . Profit Sharing Policy. . Unlimited PTOs after your first year (20 PTOs the first year). . Equipment for your setup. . Great work/life balance. . Honest, simple, and transparent culture. . US-based clients and international teams. . .  . . Everyone has a story. We're eager to hear yours and help you write the next chapter. . . Are you ready for a change?. #Wearethechange. !