Key Facts

Remote From:

Anywhere

Full time

Senior (5-10 years)

English

Hard Skills

Other Skills

•
Team Leadership
•
Adaptability
•
Dealing With Ambiguity
•
Problem Solving
•
Decisiveness
•
Strategic Planning
•
Creativity

Roles & Responsibilities

8+ years of progressive experience in DataOps engineering with a track record of building and optimizing data pipelines and automation frameworks
Deep expertise in data warehousing, data lakes, and distributed processing technologies (e.g., Spark, Hadoop, Kafka)
Expert-level programming skills (SQL, Python, Java/Scala) and deep experience with microservices architecture, containerization (Docker, Kubernetes), and IaC (Terraform, CloudFormation)
Preference for native GCP stack; AWS and Azure experience considered

Requirements:

Lead DataOps strategy and architecture for multiple projects globally, driving automation, data quality, CI/CD, and reliability.
Architect and promote microservices-based data platforms with containerization and Infrastructure as Code to ensure scalability and resilience.
Oversee the development of self-service data infrastructure platforms to enable rapid deployment, scalability, and reliability through automation and intelligent workflows.
Mentor and coordinate cross-functional squads, aligning data architecture with business goals and ensuring observability and governance.

Quantix, Inc.

About Quantix, Inc.

Quantix is an IT workforce management services provider that prioritizes people and purpose for growth. Pioneering the road map for changing the culture in the IT services industry. Quantix believes in unleashing the power of human potential, embracing diversity, and helping people and organizations thrive in reshaping our economy and the world. Quantix is on a mission to set a new standard for business to create a more inclusive reality for individuals and teams by supporting organizations that create the type of workplace where people feel motivated to contribute in a way that fuels bottom-line growth. Since 2002 we've been providing contract, contract-to-hire and direct hire services to a wide range of clients. We provide individual consultants, project management, project teams and executive management placements.

Founded: 2018

Company size: 51 - 200

Website LinkedIn See all jobs →

Job description

Title: Staff Data Operations (DataOps) Engineer
Location: 100% Remote
Tiem Zone: CST
Hours: Approximately 50 hours/week
Type: Direct hire
Salary range: 180 – 220K

Job Description: We're seeking a visionary and very senior-level Staff DataOps Engineer to lead this transformation, pioneering DataOps excellence at a global scale and driving the adoption of next-generation microservices architectures with a relentless focus on automation. We are committed to implementing and evolving leading DataOps practices to ensure the highest levels of data reliability and efficiency. Our platform squads are at the forefront of this evolution, creating self-service products that democratize infrastructure, enabling rapid deployment, scalability, and reliability through sophisticated automation, Continuous Integration and Continuous Delivery, and Data Quality practices. We thrive on tackling complex challenges, leveraging creativity, decisiveness, and adaptability to navigate ambiguity and deliver transformative solutions through automated workflows and intelligent systems. If you're passionate about shaping the future of data and building platforms that empower entire organizations with the power of automation, join us at Lore and be a catalyst for innovation.

*they are looking for the type of person that will be able to lead the team and architecture of multiple projects at once from a strategic standpoint, not just single project work.

Requirements:

8+ years of progressive experience in DataOps engineering, with a proven track record of implementing and optimizing data pipelines and automation frameworks.
Deep expertise in data warehousing, data lakes, and distributed data processing technologies (e.g., Spark, Hadoop, Kafka).
Exceptional proficiency in programming languages (e.g., SQL, Python, Java, Scala).
Prefers native GCP Stack as they are not changing their technologies. Others might be considered (AWS and Azure).
Expert-level understanding of microservices architecture and containerization technologies (e.g., Docker, Kubernetes).
Deep understanding and experience with Infrastructure as Code (IaC) tools (e.g., Terraform, CloudFormation).
Proven ability to architect and implement highly scalable and resilient data solutions.
Advanced understanding of data orchestration, monitoring, and observability tools.
Proven ability to create and implement data automation frameworks.
Experience with real time data platforms at extreme scale.
Strong understanding and experience with CI/CD methodologies and tools for data pipelines, including automated testing and deployment.
Experience with data quality tools, and monitoring systems.
Experience with DataOps related tooling.