Data / Analytics Engineer
We are looking for a Data / Analytics Engineer to join an ongoing initiative focused on building a scalable, AI-driven data platform for product analytics.
This is a new role within an existing analytics team, where youβll help architect and build the core data layer that will enable self-service analytics across the company. The role combines hands-on data engineering with forward-looking AI automation initiatives.
Client/Project: is a global DevOps company.
The project focuses on building a Gold data layer that enables product and business stakeholders to access ready-to-use, reliable datasets without relying on ad-hoc requests.
Itβs a complex and high-impact domain, where:
- you will design and build a scalable data model from multiple sources (Snowplow, FullStory, internal systems)
- the team is transitioning to an AI-first development approach (Cloud Code, Codeium - no manual SQL writing mindset)
- AI agents are a core part of the vision (automating data transformations and schema evolution)
- the work has a direct impact on decision-making across a ~600-person product organization
Cooperation: full-time, short-term (6 months with the high possibility of prolongation)
Stage: existing (early stage of data platform transformation - Gold layer not yet built)
Position: new
Timezone requirements: CET Β±2h preferred
Location requirements: Remote
Client team: Analytics Guild (up to 9 people)
English: Upper-Intermediate+
Requirements:
- 4+ years of experience in Data Engineering / Analytics Engineering (Mid+ or Senior level)
- Strong SQL skills (advanced: window functions, CTEs, joins, performance tuning)
- Hands-on experience with dbt (models, testing, documentation)
- Experience with Amazon Redshift (or strong AWS DWH background)
- Solid understanding of data modeling (dimensional modeling, medallion architecture)
- Experience with Python for data pipelines, integrations, or data quality
- Practical experience using AI coding tools (Copilot, Codeium, Claude, etc.) in daily work
- Experience working with product/event data
- Strong ownership and ability to work autonomously
- Clear communication skills and the ability to work with non-technical stakeholders
Nice to have:
- Experience building or experimenting with AI agents (LangChain, OpenAI API, etc.)
- Familiarity with Snowplow or similar event tracking tools
- Familiarity with FullStory or behavioral analytics tools
- Experience with AWS ecosystem (S3, IAM, etc.)
- Experience with orchestration tools (e.g., Airflow)
- Understanding of BI tools (e.g., Looker) and data consumption patterns
Responsibilities:
This role evolves in two main phases:
Phase 1 (Months 1-4): Building the Gold Layer
- Design and implement Gold-layer data models in dbt
- Transform raw and Silver-layer data into business-ready datasets
- Integrate multiple data sources (Snowplow, FullStory, internal systems)
- Collaborate with the analytics team to translate business needs into reusable models
- Identify and fix inconsistencies in existing data layers
- Establish data quality, monitoring, and observability practices
Phase 2 (Months 4-6+): Automation & AI
- Design and build AI agents for automating data workflows
- Develop systems that detect new incoming events and suggest schema placement
- Automate maintenance of the Gold layer
- Explore and implement AI-driven approaches for data transformations
Ownership areas:
- Gold data layer architecture
- Data quality and reliability
- AI-driven automation of data workflows
- Collaboration with analytics stakeholders
- Long-term scalability of the data platform
Benefits from 8allocate:
- Team & Culture: Team events, offsites, and a culture that keeps people connected.
- Learning & Development: Budget for courses, certifications, and conferences.
- Wellbeing: Flexible support in line with company policy, with options to support your physical and mental well-being (sport, mental health, or medical insurance).
- Rest & Recovery: Paid vacation and sick leave.
Required skills experience
| Advanced SQL | 4 years |
| dbt | 4 years |
| Data Modeling (dimensional / medallion) | 4 years |
| AI-assisted development (practical usage) | 2 years |
Required languages
| English | B2 - Upper Intermediate |
| Ukrainian | Native |