TRCI-26-06115

Senior Data/ML Engineer (Python, Snowflake/dbt, Azure AI/LLM)

Senior (8–10 years) contract engineer in Poland combining strong Python engineering with modern data platform skills (Snowflake/Spark, advanced SQL, dbt, orchestration, CI/CD) and applied ML/LLM delivery on Azure. The role covers building production-grade pipelines and models, optimizing Snowflake performance/cost, implementing governance (RBAC), and delivering LLM applications/agents (RAG, LangChain/LlamaIndex) plus document AI/OCR workflows. Expect hands-on MLOps (MLflow, Azure ML, GitHub Actions/Azure DevOps, IaC) and containerized deployments (Docker, ACA/ACR), with senior ownership of standards, code reviews, and incident troubleshooting.

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Position summary

Location: Poland
Workplace: Remote
Employment: Contract
Experience: Minimum 8 years and Maximum 10 years

Apply now

Role overview

Why This Role Matters.

Your Impact

Deliver Enterprise Value

Help organisations solve complex business problems through modern technology, consulting expertise and measurable outcomes.

Collaboration

Work Across Teams

Collaborate with consultants, architects, engineers and client stakeholders throughout the project lifecycle.

Growth

Learn Continuously

Gain exposure to enterprise technologies, certifications, mentoring and real-world project experience.

Career Path

Grow With Ubique

Build a long-term consulting career with opportunities to take on greater responsibility and leadership over time.

Responsibilities

What You'll Be Doing.

Every role at Ubique contributes directly to solving meaningful business challenges for our clients.

Technical roadmap ownership / architecture decisions

Setting engineering standards (code review bar, testing standards) across both DE and DS work

Ability to review code/PRs and mentor junior engineers

Stakeholder communication (translating technical concepts to business users)

Documentation and knowledge-sharing practices

Cost optimization mindset (especially critical in Snowflake/Azure environments)

Cross-functional collaboration with analytics, BI, and data science teams

Incident management and troubleshooting production data issues

Technology stack

Tools & Technologies.

The platforms and technologies you'll use to build modern, enterprise-grade solutions.

Python

Required

SQL

Required

Snowflake

Required

Spark

Required

dbt

Required

Jinja

Required

Airflow

Required

Azure Data Factory

Required

Dagster

Required

Git

Required

GitHub

Required

Azure Repos

Required

GitHub Actions

Required

Azure DevOps

Required

MLflow

Required

Azure Machine Learning

Required

Azure AI Studio

Required

Azure OpenAI Service

Required

Azure AI Foundry

Required

Azure AI Search

Required

Requirements

Skills & Experience.

We value curiosity, collaboration and continuous learning. If you don't meet every requirement but believe you can make an impact, we'd still love to hear from you.

Essential

Required Qualifications

Python (production-quality code)

SQL (advanced: window functions, CTEs, recursive queries)

Snowflake (large-scale datasets; performance tuning; cost optimization)

Spark and/or Snowflake experience with large-volume datasets

Bash scripting/automation

Git (branching strategies, PR workflows, code review)

Data lake vs data warehouse concepts; medallion architecture (bronze/silver/gold)

API integration patterns for ingestion from source systems

Schema evolution; semi-structured data handling (JSON/VARIANT)

Snowflake features: Snowpipe, Streams & Tasks, Time Travel, Zero-Copy Cloning, data sharing

RBAC, security, data governance (Snowflake)

dbt (Jinja templating, macros, incremental models, snapshots/SCD2, testing/dbt-utils)

Orchestration tooling (Airflow or Azure Data Factory or Dagster)

Dimensional modeling (Kimball), star/snowflake schemas

CI/CD for data/ML pipelines (GitHub Actions or Azure DevOps)

Experiment tracking/model versioning (e.g., MLflow)

Hands-on ML on large-scale production datasets (regression/classification/clustering/ensembles; time series)

Evaluation best practices (train/val/test splits, leakage avoidance, forward/out-of-sample validation)

LLM application development (agents, tool use, orchestration) on Azure (Azure AI Foundry/model endpoints)

RAG pipelines (chunking, embeddings, vector index; Azure AI Search)

Preferred

Nice to Have

Snowpark (Python/Java integration)

Serverless compute (Azure Functions)

Infrastructure as Code (Terraform or Bicep)

Deployment strategies (blue-green, canary) and rollback automation

Basic UI prototyping (Streamlit or Gradio)

Supply chain domain experience (demand/supply planning, inventory optimization, logistics, procurement)

ERP integration/data structures (Oracle, SAP, Salesforce)

Azure API Management (API gateway)

Networking on Azure (VNet, Private Endpoints)

Large-scale model serving optimization (GPU inference, latency tuning, cost management)

What you'll gain

More Than Just A Job.

We're committed to helping every team member grow professionally, personally and technically while working on meaningful projects.

Global Exposure

Collaborate with international clients and multicultural teams on enterprise programmes.

Continuous Learning

Expand your expertise through mentoring, certifications and hands-on project experience.

Career Growth

Take ownership, develop leadership skills and grow your consulting career over time.

Flexible Working

Hybrid and remote collaboration designed around trust and delivering exceptional outcomes.

People First

Join a supportive culture where collaboration, respect and long-term relationships come first.

Enterprise Projects

Work on meaningful technology initiatives for leading organisations across industries.

Apply

Apply for Senior Data/ML Engineer (Python, Snowflake/dbt, Azure AI/LLM)

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