Senior Data Engineer

4 semanas atrás


Brazil Solfácil Tempo inteiro

Solfacil is Brazil’s leading and fastest-growing solar technology company. Today, our fintech business enables installers to efficiently help homeowners go solar by providing fast, easy, and affordable financing solutions. We combine our financing with the distribution of solar hardware kits - including panels, inverters, and batteries - to make the solar purchase and installation experience seamless for all parties. Solfacil is investing in product and technology to evolve into a world-class platform company and is looking for top-notch talent to join us on our mission.

The Senior Data Engineer will develop and deploy solutions to build a modern and innovative data platform for advanced data analysis and processing at Solfacil. In this role, you will work closely with the business and our Data Engineering team members - including analytics engineers, data analysts, business analysts, and data governance engineers - to provide the necessary infrastructure/tools to efficiently and effectively solve our most important business problems.

As a key member of the team, you will help design and build solutions that answer key questions such as: Is all our data available to the business? How do we monitor all the data pipeline jobs and show the problems to the data owners? How do we process 1TB of data to get two kinds of events that answer the business questions? How do we deliver a self-service data platform capable of ensuring end-to-end data quality and governance?

How can we empower and train our users to explore and manipulate this data autonomously while ensuring compliance with our security policies?

Join us and play a pivotal role in shaping the future of our data-driven organization.

Key Responsibilities

  1. Develop and deliver top-quality data solutions on AWS for internal customers, understanding their unique data processing requirements. Translate them into robust technical architectures, including crafting sophisticated data processing systems that adhere to business rules and constructing a curated layer and data marts.
  2. Assist business teams to automate manual processes and transition to SQL-based environments.
  3. Participate in daily standup meetings and address technical issues
  4. Support current workflows, leading and helping analytics engineers
  5. Lead and assist analytics engineers without direct supervision while maintaining detailed documentation.
  6. Design, build, and maintain a robust data ecosystem for actionable insights and informed decision-making.
  7. Ensure adherence to data governance principles, including privacy, security, and compliance requirements such as LGPD.
  8. Serve as a role model for the team.

Requirements and qualifications:

  1. 4+ years of overall work experience in data engineering, with 2+ specifically in Data lakes, and 2+ experience managing cloud-based data platforms.
  2. Proven track record of successfully completing projects, especially in designing and implementing data solutions.
  3. Demonstrated ability to ensure data quality through testing, establishing SLAs, monitoring, and alerting.
  4. Expertise in SQL, including query optimization, debugging, and database load management.
  5. Experience with data transformation tools, such as dbt (data build tool), with a deep understanding of their concepts and usage.
  6. Ability to research and recommend data frameworks and architectural/code design patterns.
  7. Basic database and data management knowledge, including Redshift and PostgreSQL expertise.
  8. Proficiency in managing data ingestion and orchestrating workflows, utilizing various ETL and ELT tools such as AirByte, Change Data Capture, Apache Airflow, and AWS Glue/PySpark.
  9. Familiarity with big data technologies, data streaming (e.g., Kafka), and real-time analytics
  10. Proficient in utilizing version control systems like GitHub.
  11. Experience in implementing data quality solutions and understanding data warehouse concepts
  12. Intermediate proficiency in English.


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