Data Lead

Job not on LinkedIn

🔥 1 minute ago

💃 Latin America – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 10%

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Cresteo

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2022

🤖 Artificial Intelligence

💼 Consulting

🏢 Enterprise

Artificial Intelligence • Consulting • Enterprise

Cresteo is a strategic technology partner that designs, builds, and operates enterprise AI solutions. They offer an AI Agentic Studio and the Cresteo Forge framework to integrate GenAI, agentic systems, LLMOps, computer vision, data & analytics, and cybersecurity into production on client infrastructure. Cresteo embeds with enterprise teams to deliver digital transformation, platform engineering, and measurable outcomes across industries such as fintech, legal, healthcare and e-learning, and emphasizes security (ISO/IEC 27001) and strong delivery metrics (reduced costs, faster time-to-market, high client retention).

📋 Description

• Lead the evolution of a production data platform built around dbt, Apache Airflow, Amazon Redshift, Python, and AWS • Take ownership of the platform's architecture, reliability, and data quality • Design, operate, maintain, and evolve production data platforms and modern data warehouse architectures • Develop and maintain software solutions across a varied technology stack • Navigate, troubleshoot, and improve complex dbt projects with hundreds of models and thousands of automated tests • Design and manage Apache Airflow DAGs, operators, task groups, sensors, variables, connections, and SLAs • Optimize Amazon Redshift schemas, distribution and sort strategies, query performance, and warehouse costs • Build and maintain ingestion processes • Manage data infrastructure through Terraform • Provide technical leadership, documentation, architecture knowledge, and knowledge transfer • Maintain and evolve a complex, business-critical data ecosystem

🎯 Requirements

• 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

🏖️ Benefits

• 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