Lead Data Engineer
Anywhere in Latin America4h ago
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Skills
About the role
We’re looking for an experienced Lead Data Engineer to design and deliver scalable, high-performance data solutions for our clients. You’ll lead data engineering initiatives, build and optimise data pipelines and models, and connect complex data sources to power analytics, customer engagement, and business decisions.
Working closely with Data, CRM, and CDP teams, you’ll bring strong technical expertise across modern data platforms, with a focus on Snowflake, SQL, Python, and dbt. You’ll also guide engineering best practices, explore new technologies and AI tools, and help clients get more value from their data infrastructure.
- Design, build, and maintain scalable ETL/ELT pipelines across batch and real-time data architectures.
- Develop and optimise data models, transformations, and workflows using SQL, Python, and dbt.
- Build and maintain integrations across cloud data platforms, warehouses, and external data sources
- Improve database performance, data reliability, and cost efficiency through monitoring and optimisation.
- Implement data quality checks, unit tests, and validation processes to maintain data integrity.
- Translate customer engagement and CRM data requirements into actionable data models and pipelines that power Braze and other platforms.
- Work with customer events, user attributes, identity resolution, and data synchronisation to support personalised customer experiences.
- Collaborate with Data, Analytics, CRM, and CDP teams to align technical solutions with client requirements and business goals.
- Provide technical leadership, guidance, and best practices to engineers and help drive continuous improvement.
- Identify opportunities to use AI tools, automation, and emerging technologies to improve engineering productivity and data workflows.
- Support multiple client engagements, communicate technical recommendations clearly, and adapt to changing priorities.
- 5+ years of experience in data engineering, data platforms, or a similar technical role, with strong ownership of architecture, implementation, and optimisation.
- 4+ years of hands-on experience with SQL, data modelling, and ETL/ELT processes.
- 2+ years of experience using Python to build data applications and transformations.
- Practical experience with dbt and modular data transformation.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud, and modern data integration tools.
- Strong understanding of data architecture, pipeline design, database performance, testing, and data quality.
- Experience translating business and customer engagement requirements into reliable data solutions.
- Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Experience working in an agency or consulting environment, managing multiple clients and adapting to changing priorities.
- A proactive approach to problem-solving, continuous learning, and using AI tools to improve day-to-day productivity.
- Ability to work independently while collaborating effectively with cross-functional teams.
- Strong written and verbal English communication skills (C1 level or equivalent).
Desirable
- Hands-on experience with Snowflake, Hightouch, mParticle, or Databricks.
- Snowflake SnowPro Advanced: Architect or Data Engineer certification.
- Experience with customer data platforms (CDPs), identity resolution, audience activation, and real-time data synchronisation.
- Familiarity with Braze, CRM platforms, and customer engagement data models.
- Experience with other cloud data warehouses, such as BigQuery or Redshift.
- Knowledge of data visualisation tools such as Power BI or Tableau.
- Understanding of data governance, privacy, security, and access controls.
- Exposure to AI/ML architectures, cloud-native AI services, or agentic workflows.
- Experience working in Agile or Scrum environments.