DataOps Engineer

Bridgenext; Argentina; Presencial; ARS 1.800.000 - 3.000.000; Jornada completa

Descripción de la vacante

Bridgenext, a digital consulting services leader, is seeking a Data Operations Engineer with deep Snowflake and Apache Airflow expertise to join our team. You will design, build, and optimize data ingestion and transformation workflows, ensuring reliability across production pipelines.

You’ll own on-call rotations, contribute to CI/CD with Terraform, collaborate with platform teams, and apply Python scripting to automate tasks, monitoring, and incident response.

Formación

• Snowflake environments, performance tuning, data loading.
• DAGs, pipelines design and troubleshooting in Airflow.
• Relational databases such as MS SQL and Postgres.
• Kafka Connect and Debezium exposure is a plus.

Responsabilidades

• Data Pipeline & Workflow Management: Design, build, schedule, monitor, and optimize data ingestion and transformation workflows using Apache Airflow.
• Snowflake Data Warehousing: Support Snowflake development and operations, including data modeling, schema management, performance tuning, warehouse optimization, data loading, and troubleshooting production data issues.
• Airflow Operations & Reliability: Maintain, troubleshoot, and enhance Airflow workflows by investigating DAG failures, improving task observability, strengthening alerting, and ensuring reliable pipeline execution during business hours and on-call rotations.
• Infrastructure & CI/CD Growth: Partner with platform teams to contribute to our GitHub CI/CD workflows, Pull Request reviews, and Terraform-managed infrastructure (module maintenance).
• Monitoring & Reliability: Maintain and improve monitoring and alerting infrastructure using tools like New Relic, Grafana, and PagerDuty to ensure pipeline health.
• Container Maintenance: Troubleshoot and support existing Kubernetes/Helm deployments with guidance from senior platform engineers.
• Operational Excellence: Write clear runbooks to document operational procedures, replacing tribal knowledge with structured guides.
• Automation: Utilize Python to build helper scripts, automate data processing tasks, and streamline infrastructure management.

Conocimientos

Snowflake

Apache Airflow

Databases

Streaming & CDC

Herramientas

GitHub

Terraform

New Relic

Grafana

PagerDuty

Kubernetes

Helm

Python

Descripción del empleo

Company Overview
Bridgenext is a digital consulting services leader that helps clients innovate with intention and realize their digital aspirations by creating digital products, experiences, and solutions around what real people need. Our global consulting and delivery teams facilitate highly strategic digital initiatives through digital product engineering, automation, data engineering, and infrastructure modernization services, while elevating brands through digital experience, creative content, and customer data analytics services.

Company Overview
Bridgenext is a digital consulting services leader that helps clients innovate with intention and realize their digital aspirations by creating digital products, experiences, and solutions around what real people need. Our global consulting and delivery teams facilitate highly strategic digital initiatives through digital product engineering, automation, data engineering, and infrastructure modernization services, while elevating brands through digital experience, creative content, and customer data analytics services.
Don't just work, thrive. At Bridgenext, you have an opportunity to make a real difference - driving tangible business value for clients, while simultaneously propelling your own career growth. Our flexible and inclusive work culture provides you with the autonomy, resources, and opportunities to succeed.
Position Description
We are looking for a talented and experienced Data Operations Engineer to join our team. Bridgenext is seeking a Data operations engineer with deep expertise in Snowflake and Apache Airflow, who is also ready to take on infrastructure and operational responsibilities.
You would be working in Central US Business hours, and you would also be part of the team which provides on-call support for high priority production issues.
Key Responsibilities

• Data Pipeline & Workflow Management: Design, build, schedule, monitor, and optimize data ingestion and transformation workflows using Apache Airflow, including DAG development, dependency management, retries, and failure handling.
• Snowflake Data Warehousing: Support Snowflake development and operations, including data modeling, schema management, performance tuning, warehouse optimization, data loading, and troubleshooting production data issues.
• Airflow Operations & Reliability: Maintain, troubleshoot, and enhance Airflow workflows by investigating DAG failures, improving task observability, strengthening alerting, and ensuring reliable pipeline execution during business hours and on-call rotations.
• Infrastructure & CI/CD Growth: Partner with platform teams to contribute to our GitHub CI/CD workflows, Pull Request reviews, and Terraform-managed infrastructure (module maintenance).
• Monitoring & Reliability: Maintain and improve monitoring and alerting infrastructure using tools like New Relic, Grafana, and PagerDuty to ensure pipeline health.
• Container Maintenance: Troubleshoot and support existing Kubernetes/Helm deployments with guidance from senior platform engineers.
• Operational Excellence: Write clear runbooks to document operational procedures, replacing tribal knowledge with structured guides.
• Automation: Utilize Python to build helper scripts, automate data processing tasks, and streamline infrastructure management.
  

Must Have Skills (Core Data Focus)

• Snowflake: Extensive experience managing Snowflake environments, performance tuning, and data loading.
• Apache Airflow: Proven track record of building, scheduling, and troubleshooting complex DAGs and pipelines.
• Databases: Strong working knowledge of relational databases such as MS SQL and Postgres.
• Streaming & CDC (Nice to have / Exposure): Familiarity with Kafka Connect and Debezium.
  

Preferred Skills (DevOps Exposure & Willingness To Learn)

• Version Control: Comfortable using GitHub for code management, branching strategies, and PR reviews.
• Infrastructure as Code: Foundational understanding of Terraform (willingness to build and maintain modules).
• Observability: Experience or familiarity with alerting and monitoring platforms (New Relic, Grafana, PagerDuty).
• Containerization: Basic familiarity with maintaining or troubleshooting Kubernetes and Helm charts.
• Cloud & Scripting: Working knowledge of AWS or Azure, paired with strong Python scripting skills.
  

Bridgenext is an Equal Opportunity Employer