UNAVAILABLE Opportunities

Full Job Description

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 seeking a skilled and detail-oriented DataOps Engineer to design, build, and maintain automated data pipelines and cloud-based data platforms that support enterprise-scale web, mobile, and AI-driven applications. The DataOps Engineer will be responsible for ensuring the reliability, performance, and scalability of data operations, enabling smooth integration between systems, analytics, and applications. This role requires hands-on expertise with Azure data services, data orchestration tools, and CI/CD automation for data workflows.

Key Responsibilities:

• Develop, deploy, and maintain data ingestion, transformation, and delivery pipelines using Azure Data Factory, Databricks, or equivalent frameworks

• Implement CI/CD pipelines for data workflows using Azure DevOps or GitHub Actions

• Automate data quality checks, schema validation, and error handling mechanisms

• Integrate structured, semi-structured, and unstructured data sources (APIs, databases, IoT, etc.)

• Collaborate with Data Engineers, DevOps, and Developers to enable seamless data flow between systems

• Manage and optimize Azure cloud data services (Data Lake, Synapse, SQL, Blob Storage, Key Vault)

• Implement infrastructure as code (IaC) using ARM templates, Terraform, or Bicep for provisioning data resources

• Enforce data governance and access controls aligned with organizational policies

• Implement automated data quality and validation frameworks

• Build dashboards for tracking data pipeline health, latency, and throughput

• Work closely with Data Engineers, Business Analysts, and Product Teams to align data operations with business goals

• Support the data integration needs of downstream systems like BI dashboards (Power BI, Tableau) or AI applications

Workplace: Remote role in LATAM, preference for candidates based in Argentina. This role supports US-based client work and requires working Eastern timezone hours

Must-Have Skills:

• 5+ years of experience in Data Engineering or DataOps, preferably in cloud-based enterprise environments

• Strong hands-on experience with Azure Data Factory, Azure Synapse, Databricks, and Azure SQL

• Proficiency in Python, PowerShell, or Bash scripting for automation and monitoring

• Experience with Infrastructure as Code (Terraform, ARM)

• Working knowledge of DevOps tools (Azure DevOps, Git, Jenkins, GitHub Actions) for pipeline automation

• Familiarity with ETL/ELT processes, API integrations, and event-driven architectures

• Understanding of data governance, metadata management, and data lineage principles

• Strong problem-solving and analytical skills with a focus on data reliability and performance

Professional Skills:

• Solid written, verbal, and presentation communication skills

• Strong team and individual player

• Maintains composure during all types of situations and is collaborative by nature

• High standards of professionalism, consistently producing high quality results

• Self-sufficient, independent, requiring very little supervision or intervention

• Demonstrate flexibility and openness to bring creative solutions to address issues

Bridgenext is an Equal Opportunity Employer

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