Lead Data Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 2d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 6d ago
The date the source published, not the day we noticed it (2026-10-26). Last seen at its source 2h ago.
We have tracked this listing since 26 Oct 2026 (6 days). The employer's own board has carried it every time we have read it, most recently 2 hours ago.
Is it remote?
Anywhere in Latin America
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
LATAM
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $72.5k–150k/yr
Middle 50% of 85 listings that do state pay — Engineering · all levels · LATAM · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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Lever employer's own board first seen 6d ago · last seen 2h ago
The listing
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.