Backend, Data Software Engineer

🕒 June 2

🇧🇷 Brazil – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🔙 Backend Engineer

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Logo of Tenchi Security

Tenchi Security

51 - 200 employees

Founded 2019

🔒 Cybersecurity

📋 Compliance

🏢 Enterprise

💰 $3.3M Seed Round on 2021-10

Cybersecurity • Compliance • Enterprise

Tenchi Security is a cybersecurity company that specializes in third-party cyber risk management. Their unique solution, Zanshin, systematically reduces third and nth-party cyber risks by enhancing security postures through continuous monitoring and proactive remediation efforts. Recognized as a LinkedIn Top Startup in 2024, Tenchi Security focuses on building not just compliance but meaningful partnerships in cybersecurity, enabling both enterprises and their third-party vendors to collaboratively manage and mitigate risks.

📋 Description

• Backend Development: Design, build, and maintain scalable, high-performance backend services and APIs using Python. • Data Pipeline Engineering: Architect and optimize reliable ETL/ELT pipelines to process large volumes of data using PySpark. • System Architecture: Containerize applications and data jobs for seamless deployment across environments. • Data Modeling & Storage: Design efficient relational database schemas and optimize complex SQL queries for both transactional and analytical workloads. • Collaboration: Work closely with product, analytics, and data science teams to understand data requirements and deliver production-ready software solutions.

🎯 Requirements

• Python: Strong proficiency in writing clean, testable, and efficient production code (e.g., using frameworks like FastAPI, Flask, or standard library concurrency). • SQL: Advanced knowledge of SQL (joins, window functions, query optimization) and experience working with relational databases (e.g., PostgreSQL, MySQL). • PySpark & Big Data: Hands-on experience using PySpark for distributed data processing and large-scale data manipulation. • Docker: Experience containerizing applications and managing local or production deployments using Docker/Docker Compose. • Engineering Mindset: Strong grasp of software engineering best practices, including git version control, CI/CD, code reviews, and writing unit/integration tests. • Desirable (Nice-to-Have): • Experience with Apache Iceberg for managing large-scale analytic datasets and table formats. • Familiarity with cloud storage solutions and optimization techniques, specifically AWS S3 / S3 Tables. • Familiarity with data ingestion and orchestration tools (e.g., AWS Glue, AWS Step Functions).

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