[Hiring] Solution Engineer, Data & AI @Arctiq

Role Description

The Solution Engineer, Data & AI is a hands-on builder who designs, delivers, and operates production-grade data and AI solutions. You will join a team of engineers who bring real software engineering discipline to data work — version control, automated testing, CI/CD, infrastructure as code, and observability are how we work, not afterthoughts. We also expect our engineers to embrace agentic engineering, using tools like Claude Code to dramatically accelerate how software gets built without compromising quality.

Depending on business need and your strengths, you will be aligned to one of two paths:

• Path 1 — Client Delivery: Support delivery of fixed-price, outcome-based data and AI projects for clients across a wide range of industries and problem domains, on Azure, AWS, and GCP.
• Path 2 — Internal Data & Analytics: Bring order to our internal data on Azure Databricks — integrating, cleaning, and modelling data from our business systems.

Responsibilities

• Data Pipeline Engineering:
  • Design, build, and maintain reliable, scalable data pipelines for batch and streaming workloads.
  • Apply proven lakehouse architecture patterns, with clear data contracts and well-managed schema evolution.
  • Build data quality checks, testing, and monitoring into every pipeline from day one.
• Data Modelling & Analysis:
  • Design analytical data models that reflect business requirements and perform at scale.
  • Profile, explore, and analyze data to validate assumptions, surface quality issues, and share meaningful insights with stakeholders.
  • Apply sound data governance practices so data assets are secure, traceable, and discoverable.
• AI & Machine Learning Engineering:
  • Build, train, and evaluate machine learning and generative AI solutions.
  • Establish rigorous evaluation approaches tied to clear, business-aligned success criteria.
  • Take models from experimentation to production, ensuring they are reliable, observable, and maintainable.
• MLOps & DevOps:
  • Build and maintain CI/CD pipelines for code, data, and models.
  • Manage cloud and platform resources through infrastructure as code.
  • Implement full model lifecycle management — versioning, deployment, monitoring, drift detection, and retraining.
  • Champion engineering best practices across the team.
• Agentic Engineering:
  • Use agentic coding tools (e.g., Claude Code) as a core part of your daily workflow.
  • Provide AI agents with effective context through clear specifications, project instructions, and reusable workflows.
  • Apply rigorous review, testing, and validation to AI-generated code.
  • Share effective agentic workflows with the team.
• Path 1 — Client Delivery:
  • Deliver engineering workstreams on fixed-price client engagements.
  • Work across client environments on Azure, AWS, and GCP.
  • Partner with Architects and your Engineering Manager to deliver solutions within agreed scope, timeline, and commercial constraints.
  • Participate in client workshops, demos, and technical working sessions.
  • Identify scope creep, technical risks, and blockers early.
  • Leave clients better off: document solutions clearly, transfer knowledge, and help build client-side capability.
  • Contribute to reusable accelerators, templates, and patterns.
• Path 2 — Internal Data & Analytics:
  • Integrate data from our core business systems into our Azure Databricks environment.
  • Clean, reconcile, and standardize messy internal data.
  • Coordinate with internal teams to identify, prioritize, and resolve data quality issues.
  • Build trusted, well-documented data models that power internal analytics.
  • Partner with Finance, Sales, Operations, and leadership to understand reporting needs.
  • Help design and automate quote-to-cash workflows.

Qualifications

• 4+ years in software and platform engineering, including meaningful time on a collaborative software development team.
• Hands-on experience building production data and ML solutions in the cloud.
• Strong, demonstrable experience with the Databricks platform in production environments.
• Practical experience using agentic coding tools to accelerate software development.

Requirements

• Technical Skills:
  • Software Engineering & DevOps:
    • Strong proficiency in Python and SQL.
    • Solid software engineering fundamentals.
    • Hands-on experience with CI/CD tooling and infrastructure as code.
    • Comfortable with containerization and automated deployment.
  • Cloud Platforms:
    • Working knowledge of Azure, AWS, and GCP.
    • Understanding of how data platforms are deployed and integrated on each cloud.
  • Databricks:
    • Deep, hands-on experience across the Databricks platform.
    • Experience deploying and managing Databricks solutions using software engineering and DevOps best practices.
  • Data Engineering & Modelling:
    • Proven ability to design and build scalable batch and streaming pipelines.
    • Strong data modelling skills across dimensional and modern lakehouse patterns.
  • AI / ML & MLOps:
    • Practical experience building, evaluating, and deploying ML models to production.
    • Experience with generative AI patterns.
  • Agentic Engineering:
    • Hands-on proficiency with agentic development tools.
    • Ability to decompose work, write clear specifications, and manage context.

Company Description

Arctiq is a global, intelligence-driven technology services company delivering professional and managed services across Hybrid Cloud Infrastructure, Networking & Connected Experiences, Cybersecurity, Data & AI, Autonomous Operations & Intelligence, and Enterprise Service Management.

We help organizations operate, secure, and modernize complex environments by unifying infrastructure, networking, data, security, automation, and observability under a single, integrated operating model.

Our work focuses on helping customers reduce operational friction, improve resilience, and make better, faster decisions as their environments evolve.

Arctiq builds on decades of industry expertise and a customer-centric ethos to deliver exceptional value to clients across diverse industries.