3 melhores vagas de full stack developer (python) (Contratando agora!)

Senior Data Engineer ID81743
AgileEngine —Remoto
- Tempo integral
- Home Office
- CRM software
- Azure
- Gestão
Candidatura rápida
15 h
Engineering Manager, Automations & Internal Tooling
Fivetran —Rio Grande do Sul
- Tempo integral
- Bar
- Java
- Desenvolvimento de Software
Candidatura rápida
19 h
Software Engineering - Distributed Agentic AI Systems
HP —Porto Alegre, RS
- Tempo integral
- Ciência da Computação
- Ciência da Computação
- DevOps
3 h

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Engineering Manager, Automations & Internal Tooling
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Experience measuring developer productivity, engineering effectiveness, or the business impact of internal tooling. 100% employer-paid medical insurance*.
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Sua missão é nos levar ainda mais longe. Mantenha-se suficientemente envolvido para tomar boas decisões sem se tornar um gargalo. Day Off no mês de aniversário;

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Senior Data Engineer ID81743

AgileEngine -
Remoto

Candidatura rápida

Detalhes da vaga

Tempo integral
Há 15 horas

Qualificações

CRM software
Ajuste de Desempenho
Power BI
Azure
Gestão
DevOps
Inglês
SQL
RBAC
Terraform
REST
DNS
GitHub
APIs
Agile
SaaS
Python

Descrição completa da vaga

About the role

We are looking for a Senior Data Engineer to architect and build an enterprise data platform from the ground up on Snowflake and Azure, owning the full stack from infrastructure provisioning through pipeline development, data modeling, governance, and observability. You will build Bronze/Silver/Gold data models using SQLMesh, provision all platform resources with Terraform, implement CI/CD pipelines via GitHub Actions, and enforce HIPAA-aligned data handling and Snowflake RBAC standards. The role is a solo senior contributor position requiring high ownership and the ability to deliver production-grade platform without specialist support teams.

What you will do

Develop and maintain scalable data pipelines ingesting from enterprise source systems (EHR, ERP, CRM, SaaS, PMS) into Snowflake using Azure Data Factory, Azure Event Hub, and ADLS Gen2.
Build and optimize analytics-ready data models (Bronze/Silver/Gold layers) using SQLMesh.
Provision and manage all platform infrastructure through Terraform, including Snowflake objects, Azure resources, networking components, and access controls, following infrastructure-as-code standards.
Implement CI/CD pipelines using GitHub Actions for automated testing, environment promotion, and controlled multi-environment releases (dev/test/staging/production).
Design and enforce data governance, security, and access control standards, including Snowflake RBAC, row-level security, column masking, and HIPAA-aligned data handling practices.
Configure and maintain cloud networking and private connectivity, including Azure Private Endpoints, Private Link, Private DNS zones, managed identities, and network security groups.
Build and operate platform-wide observability using Datadog or equivalent, covering pipeline health, data freshness, anomaly detection, alerting, and end-to-end data lineage.
Write production-grade Python for ingestion utilities, data quality frameworks, and platform integrations, including reconciliation checks and automated tests that block bad data from reaching production.
Apply Agile delivery practices including sprint planning, standups, and backlog refinement in collaboration with analytics and business stakeholders.
Establish and document data engineering standards, reusable patterns, and best practices that scale with the platform and organization.
Diagnose and resolve production issues across pipelines, infrastructure, networking, security, and platform services.

Must haves

4+ years of hands-on data engineering experience with full production pipeline ownership in a lean, high-ownership environment (you build it, you own it, you support it).
Proven track record building and managing cloud data platforms, featuring deep expertise in Snowflake administration and performance tuning.
Strong SQL and data modeling fundamentals, including Kimball methodology, dimensional design, and Slowly Changing Dimension (SCD) management.
Production experience with SQLMesh or DBT operating in a warehouse-centric architecture.
Hands-on experience ingesting data from REST APIs and SQL Server using Azure Data Factory (ADF) and Azure Functions.
Hands-on experience using Terraform for infrastructure provisioning, paired with robust CI/CD experience using GitHub Actions, Azure DevOps, or equivalent.
Proven ability to rapidly audit, take over, and operate an existing data platform built by a third-party vendor.
Upper-intermediate English level.

Nice to haves

Experience with Power BI, including building or supporting semantic models and paginated reports.
Healthcare domain knowledge, including familiarity with dental, medical, or HIPAA-regulated data environments.
Experience with Azure VNet integration, including configuring virtual network peering, service endpoints, or VNet-injected resources.

Perks and benefits

Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
Well-being & support: access local well-being programs and people-focused support tailored to your location

Job Type: Full-time

Work Location: Remote

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Senior Data Engineer ID81743

Engineering Manager, Automations & Internal Tooling

Software Engineering - Distributed Agentic AI Systems

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