Coderio designs and delivers scalable digital solutions for general companies.
We combine strong technical expertise with a product mindset to lead complex software initiatives end-to-end.
We work with international clients, value autonomy and clear communication, and build long‐term partnerships through technical excellence.
More information: This is a high-impact technical role.
We are looking for a motivated and adaptive DataOps Engineer, Technical Referent to join our fast-paced environment.
You will operate at the intersection of data engineering, cloud infrastructure, and DevOps, where a high tolerance for ambiguity and a passion for constant learning are essential.
Your primary mission involves interacting with customers to understand their needs, extract requirements, and both design and propose scalable solutions.
You will be responsible for tackling the challenge of working within a team to develop solutions, as well as executing hands‐on technical work to ensure robust data operations.
What To Expect In This Role (Responsibilities) Automation & Integration: Develop Python components, Terraform modules, and pipelines to integrate and automate various tools and processes.
API & System Orchestration: Promote the use of APIs from distinct systems to extract and update data, trigger and monitor processes, and help tie infrastructures together.
Cloud Reliability & Operations: Deploy, maintain, and oversee cloud infrastructure to ensure it runs with the performance and reliability our customers expect.
Data Modeling & Documentation: Help create Data Models, technical documents, and best practices for our users.
DataOps Best Practices & Innovation: Develop policies, processes, and best practices regarding DevOps and DataOps.
You will also help identify opportunities, generate innovative solutions, and improve existing product features.
Requirements Development & Scripting: Strong proficiency in Python and bash, and flerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.
Competitive compensation : We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.
A selection of exciting projects : Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.
Flextime : Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.
Job Description
AgileEngine is an Inc. **** company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries.
We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
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ABOUT THE ROLE
We are looking for a part-time Data Engineering and Infrastructure Lead to audit AWS architecture, CI/CD processes,



and ETL pipeline decisions in an advisory capacity.
This person weighs managed tooling against custom builds, reviews SageMaker-based MLOps pipelines, and mentors the team on engineering standards.
Evaluating AI-assisted development workflows is part of the role.
WHAT YOU WILL DO
Audit the current AWS architecture across live applications (MAT / Signal IQ and the Impact Engine), including ECS/ECR, RDS (Postgres), S3, VPC, CloudFront/SSO, and SageMaker-based MLOps pipeline design.
Review the CI/CD process and end-to-end app development lifecycle, recommending SDLC governance layers (schema versioning, environment separation, release gating).
Evaluate how the team uses Claude Code (PR generation, automated reviews, token/cost management) to confirm output meets professional engineering standards.
Provide an early technical opinion on ETL / data-ingestion pipeline architecture (managed ELT tooling vs. custom build).
Mentor and accelerate the day-to-day infrastructure build team, focusing on AWS, DevOps, CI/CD, and data engineering practices.
Set out recommendations and technical direction where the audit surfaces necessary changes to the current build.
Report findings and recommendations directly to leadership, framing high-level risk and readiness.
MUST HAVES
6+ years of deep, current hands-on experience with AWS: ECS/Fargate, ECR, RDS (Postgres), S3, SageMaker, EventBridge, VPC/ALB/CloudFront, IAM.
Fluency in Infrastructure-as-code, specifically Terraform.
Proven track record designing or auditing CI/CD pipelines and SDLC governance (e.g., Alembic for schema/version control, environment separation, release gating).
Strong data engineering depth to provide defensible opinions on ETL / ingestion architecture (managed tools vs. custom builds).
Experience evaluating AI-assisted / LLM-assisted development workflows (e.g., Claude Code) from an engineering-quality and cost-governance standpoint.
Comfortable operating in a part-time advisory capacity (50% stepping down to 25%) as a strong communicator who can mentor less experienced engineers.
Upper-intermediate English level.
NICE TO HAVES
Prior experience working with small, fast-moving engineering teams.
Understanding of MLOps pipelines and data science infrastructure.
Media/AdTech domain knowledge is helpful but not required.
PERKS AND BENEFITS
Professional growth : Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.
Competitive compensation : We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.
A selection of exciting projects :



Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.
Flextime : Tailor your schedule for an optimal work-life balance, by having the option.
You'll combine data engineering, software engineering, solution architecture, cloud infrastructure, and technical consulting .
A major part of your mission will be building and evolving connectors and ingestion pipelines capable of integrating data from complex enterprise environments while maintaining reliability, scalability, security, and fast time‐to‐production.
What You'll Be Doing Design, develop, and maintain production‐grade data collectors, connectors, and ingestion services .
Integrate enterprise data sources including identity providers, cloud platforms, SASE solutions, network infrastructure, endpoints, applications, security platforms, and SIEM systems .
Work directly with enterprise customers to understand their environments, data flows, APIs, security requirements, and integration constraints.
Participate in technical onboarding processes, from initial discovery and architecture design through production deployment.
Design scalable ingestion architectures for processing security events, logs, identity activity, network telemetry, and other high‐volume data sources .
Build integrations using REST APIs, cloud‐native services, event‐driven architectures, and modern software engineering practices .
Develop backend services primarily using Python and/or Go .
Work with SQL and NoSQL databases to store, transform, query, and analyze high‐volume data.
Build and operate containerized services using Docker and Kubernetes .
Deploy and integrate solutions across AWS, Azure, and GCP environments .
Troubleshoot complex customer deployment and integration issues across application, infrastructure, networking, API, and data layers.
Optimize ingestion performance, reliability, scalability, and operational efficiency.
Collaborate with Solution Architects, Sales Engineering, Customer Success, Product, and Engineering teams.
Act as a trusted technical advisor around customer data architecture, collection strategies, security integrations, and implementation best practices.
Identify recurring customer requirements and transform them into reusable connectors, platform capabilities, or improvements to the core product.
Contribute technical insights from real‐world implementations to the product roadmap.
Support production adoption and continuously improve time‐to‐value for enterprise customers.
Participate in occasional customer‐facing technical sessions and, when necessary, onsite engagements.
What You Bring 10+ years of professional Software Engineering, Data Engineering, Platform Engineering, or related experience.
Strong software development experience with: Python Go Strong experience designing and consuming REST APIs .
Hands‐on experience building data ingestion pipelines, connector frameworks, integration platforms, or similar systems .
Experience integrating complex enterprise systems and third‐party platforms.
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