Senior-level Backend Software Engineering Services (Reporting)

Jobgether; Teletrabalho; BRL 418.000 - 629.000; Tempo integral

Resumo da oferta

A leading analytics firm is seeking a highly skilled Backend Software Engineer specializing in data reporting. This remote position involves building and maintaining data models using SQL and Python, transforming raw data into actionable insights, and collaborating closely with stakeholders. The ideal candidate will have over 5 years of relevant experience and strong problem-solving skills. This role offers autonomy and the chance to significantly impact customer-facing analytics and reporting solutions.

Serviços

Flexible work location in Brazil

Professional growth opportunities

Access to cutting-edge tools

Qualificações

• 5+ years of experience working with data in software environments.
• Mastery of SQL and Python for data modeling and transformation.
• Experience with OLAP datastores and schema-less databases.

Responsabilidades

• Build and maintain data models using SQL and Python.
• Implement validation checks and automated testing procedures.
• Collaborate with stakeholders for business logic and reporting requirements.

Conhecimentos

SQL

Python

Data modeling

Data integrity testing

Problem-solving skills

Collaboration

Ferramentas

DBT

GCP

AWS

Terraform

Dagster

Airflow

Descrição da oferta de emprego

We are seeking a highly skilled Backend Software Engineer specializing in data reporting to join a fast-paced analytics team. In this role, you will build and maintain composable data models, optimize SQL queries, and develop Python APIs to serve high-quality data to customer reporting interfaces. You will transform raw data into actionable business insights, collaborate closely with stakeholders, and ensure data integrity through rigorous testing and validation. This position emphasizes both technical expertise and strategic impact, enabling better decision-making through accurate and timely reporting. You will work autonomously while shaping the data infrastructure, applying software engineering best practices to maintain a scalable and reliable environment. This is a remote, high-impact role that directly supports customer-facing data solutions and analytics initiatives.

Accountabilities

• Build, optimize, and maintain data models using SQL and Python to support customer reporting interfaces.
• Apply software engineering principles such as version control, continuous integration, and automated testing to the analytics codebase.
• Transform raw data into clean, actionable insights while ensuring data quality and integrity.
• Implement validation checks and automated testing procedures across data transformation and API layers.
• Collaborate with stakeholders to define business logic, data expectations, and reporting requirements.
• Lead initiatives including problem definition, scoping, design, and planning for data infrastructure improvements.
• Develop tools and automation for managing large-scale data migrations and supporting the analytics ecosystem.

Requirements

• 5+ years of experience working with data in software environments.
• Mastery of SQL and Python for data modeling and transformation.
• Advanced experience with business semantic layer tooling, data catalog tools, and data integrity testing frameworks.
• Hands‑on experience with DBT implementation and best practices.
• Familiarity with Python API development, GCP services, and cloud‑based infrastructure (AWS, GCP, Terraform) is preferred but not required.
• Experience with OLAP datastores, DAG tooling (e.g., Dagster or Airflow), and schema‑less or document/graph databases.
• Strong ability to work autonomously, develop deep domain knowledge, and deliver high‑quality solutions independently.
• Excellent problem‑solving, collaboration, and communication skills with technical and non‑technical stakeholders.

Benefits

• Fully remote position with flexible work location in Brazil.
• Opportunity to work on high‑impact customer‑facing analytics and reporting solutions.
• Professional growth and exposure to modern data engineering practices.
• Autonomy in managing projects and shaping analytics infrastructure.
• Collaboration with cross‑functional teams in a global, innovative environment.
• Access to cutting‑edge tools and methodologies for data modeling, testing, and automation.