Senior Data Engineer / Data Engineering Technical Lead

Lever, Inc.; Brasil; Teletrabalho; BRL 180 000 - 300 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Remote work opportunity

Modern data stack exposure

Technical leadership responsibilities

Resumo da oferta

Lever, Inc. is seeking a Senior Data Engineer / Data Engineering Technical Lead based in Brazil to design scalable data platforms and lead a data engineering team.

You will build data solutions using Snowflake, dbt, Python, and ETL/ELT technologies while shaping architecture and data governance. You will collaborate with analytics, architecture, and project stakeholders to ensure reliable delivery, manage risks, and promote engineering standards across enterprise-scale initiatives.

Qualificações

• Proven experience with Snowflake, dbt and Python in data engineering.
• Strong knowledge of ETL/ELT processes and data warehousing concepts.
• Experience with data governance, quality, and metadata management is a plus.
• Familiarity with CI/CD and version control practices for data engineering.

Responsabilidades

• Design, develop, maintain, and optimize scalable data solutions and pipelines.
• Lead data engineering activities, reviews, and coding standards.
• Shape data architecture, warehousing, transformation, and integration strategies.
• Provide technical guidance and mentor data engineers across the team.
• Collaborate with architects, analysts, and stakeholders to align technical delivery with business needs.
• Identify risks, estimate work, and manage delivery plans.

Conhecimentos

Snowflake

dbt

Python

ETL/ELT

Data warehousing

CI/CD

Git

Data governance

Ferramentas

Snowflake

dbt

Python

Descrição da oferta de emprego

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer / Data Engineering Technical Lead based in Brazil.

This role combines hands-on data engineering expertise with technical leadership across modern data platforms and engineering practices. You will design and develop scalable data solutions using Snowflake, dbt, Python, and ETL/ELT technologies. The position involves shaping data architecture, pipelines, warehousing, transformation, and integration solutions that support business and reporting needs. You will also provide technical guidance to data engineers, establish development standards, and contribute to solution reviews and architectural decisions. Working closely with engineering, architecture, analytics, and project stakeholders, you will help resolve technical challenges and manage delivery risks. This is an opportunity to influence both the technical direction and delivery quality of enterprise-scale data engineering initiatives.

Accountabilities

• Design, develop, maintain, and optimize scalable data engineering solutions using Snowflake, dbt, Python, and ETL/ELT technologies.
• Build and optimize data pipelines supporting ingestion, transformation, integration, reporting, and downstream data requirements.
• Design and implement data warehouse solutions aligned with business objectives and technical requirements.
• Analyze technical requirements and recommend scalable data engineering approaches, architectures, and implementation strategies.
• Support data modeling, transformation, data quality, performance optimization, testing, deployment, and production support.
• Provide technical guidance to data engineering team members and promote consistent engineering practices.
• Define, advocate for, and implement coding standards, development practices, and data engineering best practices.
• Conduct technical reviews of data engineering solutions, code, and implementations, identifying risks, dependencies, and potential challenges.
• Break down complex technical requirements into manageable components and provide development estimates.
• Evaluate tools, frameworks, technical alternatives, and implementation approaches based on project needs.
• Collaborate with architects, developers, analysts, and project stakeholders to align technical solutions with project requirements.
• Support technical escalations, risk mitigation, issue resolution, and delivery activities.
• Prepare technical status updates and provide input into project planning, estimates, deliverables, dependencies, and delivery tracking.

Requirements

• Professional experience in Data Engineering or a closely related technical field.
• Strong hands‑on experience with Snowflake, dbt, and Python.
• Proven experience designing and developing ETL/ELT pipelines and scalable data solutions.
• Strong understanding of data warehousing concepts, architecture, data modeling, transformation, and integration.
• Ability to analyze complex technical requirements and translate them into practical, scalable data engineering solutions.
• Experience with technical troubleshooting, performance optimization, data quality, and production support.
• Experience participating in technical design discussions, solution reviews, and code reviews.
• Previous experience as a Senior Data Engineer, Data Engineering Lead, Technical Lead, or similar role is preferred.
• Experience providing technical guidance, mentoring, and knowledge sharing to other data engineers.
• Familiarity with cloud‑based data platforms and modern data stack technologies.
• Experience with CI/CD, Git, and version‑control practices for data engineering is preferred.
• Knowledge of data governance, data quality, and metadata management is an advantage.
• Experience working in Agile or structured software‑development environments.
• Strong written and verbal communication skills, with the ability to collaborate effectively across technical and business teams.

Benefits

• Remote work opportunity.
• Opportunity to work with modern data engineering technologies including Snowflake, dbt, and Python.
• Technical leadership responsibilities across data architecture, engineering standards, and solution delivery.
• Exposure to enterprise data warehousing, ETL/ELT, data modeling, and modern data platforms.
• Collaboration with engineering, architecture, analytics, and project stakeholders.
• Opportunity to contribute to technical strategy, development practices, and continuous improvement.

How Jobgether works

We use an AI‑powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top‑fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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