ETL Developer

As an ETL Developer you will be responsible for designing, developing, and optimizing data pipelines that underpin AI-powered customer operations. In this role you will play a key role in:

Designing, developing, and maintaining scalable ETL/ELT data pipelines using industry-leading tools including Apache NiFi, Apache Airflow, and Alteryx, ensuring reliable and efficient data ingestion, transformation, and loading across GCP and AWS cloud environments

Building and optimizing data workflows on Google Cloud Platform (GCP) and AWS, leveraging native cloud services to enable high-performance, secure, and resilient data processing in support of Customer Ops and AI Ops initiatives

Collaborating with data architects, AI developers, and business analysts to understand data requirements and translate them into robust pipeline designs that support Agentic AI, Conversational AI, and broader AI Ops use cases

Monitoring, troubleshooting, and optimizing existing ETL pipelines for performance, reliability, and scalability, implementing best practices in data quality, error handling, and pipeline orchestration using Airflow and related tools

Contributing to the development of data engineering standards, documentation, and reusable frameworks that accelerate delivery and improve the overall quality and maintainability of data solutions across the AI Ops practice

We are looking for an experienced and technically strong ETL Developer who is passionate about building data solutions that power AI-driven transformation. The ideal candidate will have:

7+ years of experience in ETL/ELT development, data engineering, or a related discipline, with a strong track record of delivering complex data pipeline solutions in cloud-based Customer Ops or AI Ops environments

Hands-on expertise with Apache NiFi, Apache Airflow, and Alteryx, with proven ability to design, build, and manage end-to-end data pipelines that handle large volumes of structured and unstructured data across multi-cloud environments

Strong working knowledge of Google Cloud Platform (GCP) and AWS data services, with experience designing and deploying cloud-native ETL solutions that integrate seamlessly with AI and analytics platforms

Solid understanding of data modelling, data quality frameworks, and pipeline orchestration best practices, with the ability to troubleshoot complex data issues and optimize pipeline performance in production environments

Strong communication and collaboration skills, with the ability to work effectively across cross-functional teams including data scientists, AI engineers, and business stakeholders, translating complex data requirements into efficient and scalable technical solutions

The pay range that the employer in good faith reasonably expects to pay for this position is $36.98/hour - $57.79/hour. Our benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis.

Tundra Technical Solutions is among North America’s leading providers of Staffing and Consulting Services. Our success and our clients’ success are built on a foundation of service excellence. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Unincorporated LA County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: client provided property, including hardware (both of which may include data) entrusted to you from theft, loss or damage;

return all portable client computer hardware in your possession (including the data contained therein) upon completion of the assignment, and; maintain the confidentiality of client proprietary, confidential, or non-public information. In addition, job duties require access to secure and protected client information technology systems and related data security obligations.