Data Lead

Jobtailor; São Paulo; Presencial; BRL 400 000 - 640 000; Tempo integral

Resumo da oferta

Jobtailor in São Paulo seeks an experienced Data Lead to guide the data engineering and architecture strategy. You will lead the data team, shape pipelines, models, and platform components, and set standards for governance, security, and quality.

You will work hands-on on strategic initiatives, collaborate with analytics, BI, AI, and product teams, and ensure data platform reliability while driving scalable data solutions across the organization.

Qualificações

• Advanced SQL proficiency for complex queries, optimization, and data modeling.
• Experience with relational and non-relational databases (PostgreSQL, SQL Server, MySQL, MongoDB, Redis).
• Strong Data Engineering and ETL/ELT pipeline development.
• Proficiency with Python for data engineering (PySpark, Pandas).
• Databricks platform knowledge (Delta Lake, Lakehouse, Apache Spark).
• Experience with Data Lakes, Data Warehouses, and Data Marts.
• Experience with AWS services (S3, Glue, RDS).
• Data visualization with Power BI or Tableau.
• English reading proficiency (intermediate).
• Graduate-level degree in Data Eng/Arch or related field (plus).
• Databricks/Data/Cloud certifications (plus).

Responsabilidades

• Lead the Data team both technically and functionally, serving as a reference in Data Engineering and Data Architecture.
• Develop and enhance Data Engineering solutions, pipelines, integrations, models, and platform components.
• Define, implement, and evolve architectural standards for scalability, governance, security, and data quality.
• Hands-on role in strategic initiatives and high-complexity projects.
• Support department roadmap with business needs and tech debt balance.
• Conduct code reviews and promote engineering best practices.
• Provide technical leadership to data analysts and engineers and drive growth.
• Conduct feedback sessions and support IDPs.
• Ensure reliability and availability of the company’s data platform.
• Support Analytics, BI, AI, and ML initiatives.
• Collaborate with Business, Tech, Product, and AI teams to deliver scalable solutions.
• Monitor platform performance, availability, and costs; propose improvements.

Conhecimentos

Advanced SQL Proficiency

Data Pipeline Development

ETL/ELT Development

Python for Data Engineering

Databricks Platform Proficiency

AWS Services Experience

Data Modeling

Data Visualization

Spark/PySpark

Data Lakes/Warehouses/Marts

SQL 다양한 DBs (PostgreSQL, SQL Server,My

Power BI/Tableau

Formação académica

Graduate-level degree in Data Engineering or Data Architecture

Databricks Certified Data Engineer

Microsoft Azure Data Engineer Associate

Data and Cloud Computing Certifications

Ferramentas

PostgreSQL

SQL Server

MySQL

MongoDB

Redis

Power BI

Tableau

Apache Spark

PySpark

Pandas

Descrição da oferta de emprego

• Lead the Data team both technically and functionally, serving as a reference in Data Engineering and Data Architecture
• Develop and enhance Data Engineering solutions, actively contributing to the creation of pipelines, integrations, models, and platform components
• Define, implement, and evolve architectural standards, ensuring scalability, performance, governance, security, and data quality
• Take a hands‑on role in strategic initiatives and projects with greater technical complexity
• Support the definition of the department roadmap, balancing business needs, technological advancement, and technical debt
• Conduct code reviews, support technical decisions, and promote development and engineering best practices
• Provide technical leadership to data analysts and engineers, fostering technical excellence and the team’s continuous growth
• Conduct feedback sessions, follow‑up meetings, and support the development of Individual Development Plans (IDPs)
• Ensure the reliability and availability of the company’s data platform and analytical assets
• Support Analytics, Business Intelligence, Artificial Intelligence, and Machine Learning initiatives
• Partner with Business, Technology, Product, and AI teams to transform strategic needs into scalable and sustainable solutions
• Monitor platform performance, availability, and costs, proposing continuous improvements

Requirements

• Previous experience as a Tech Lead, Technical Lead, Data Architect, or in an equivalent position
• Advanced SQL proficiency for building complex queries, optimizing performance, and data modeling
• Experience with relational databases (PostgreSQL, SQL Server, MySQL) and non‑relational databases (MongoDB, Redis)
• Strong experience in Data Engineering and ETL/ELT pipeline development
• Advanced knowledge of Python applied to Data Engineering, particularly using PySpark and Pandas
• Proficiency with the Databricks platform, including Lakehouse, Delta Lake, and Apache Spark
• Experience with modern data architectures, such as Data Lakes, Data Warehouses, and Data Marts
• Experience with AWS services, especially Amazon S3, AWS Glue, and Amazon RDS
• Knowledge of data visualization tools, such as Power BI and Tableau
• Experience integrating data for Artificial Intelligence and Machine Learning projects
• Intermediate English proficiency for technical reading
• Graduate‑level degree in Data Engineering, Data Architecture, or a related field (a plus)
• Certifications in Data and Cloud Computing (a plus)
• Databricks Certified Data Engineer certification (a plus)
• Microsoft Azure Data Engineer Associate certification (a plus)
• Experience modernizing data platforms and working on Generative AI initiatives (a plus)
• Experience in high‑volume environments and data‑oriented architectures (a plus)

Core Competencies

Demonstrates expertise in Data Engineering and Data Architecture, with a strong focus on developing scalable data solutions, optimizing performance, and ensuring data quality. Proficient in leading technical teams and fostering continuous growth while supporting strategic initiatives in analytics and machine learning.

Highest‑signal resume keywords

• Data Engineering
• Advanced SQL Proficiency
• Python for Data Engineering
• Databricks Platform Proficiency
• AWS Services Experience

ATS Optimization Keywords

Hard Skills

• Data Pipeline Development
• ETL/ELT Development
• Data Modeling
• Data Visualization
• Data Lake Architecture
• Data Warehouse Architecture
• Data Mart Architecture
• Performance Optimization
• Machine Learning Integration
• Generative AI Initiatives

Soft Skills

• Technical Leadership
• Team Development
• Feedback Facilitation
• Strategic Initiative Support
• Collaboration

Certifications & Qualifications

• Databricks Certified Data Engineer
• Microsoft Azure Data Engineer Associate
• Data and Cloud Computing Certifications

Industry Keywords

• Data Governance
• Data Quality
• Data Platform Reliability
• High‑Volume Environments
• Data‑Oriented Architectures

Tools & Technologies

• PostgreSQL
• SQL Server
• MySQL
• MongoDB
• Redis
• Power BI
• Tableau
• Apache Spark
• PySpark
• Pandas