Data Lead

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.