Data Engineer (AI)

TL;DR

Data Engineer (AI): Taking end-to-end ownership of the data platform, building and maintaining reliable pipelines into the Data Lake and datasets that are trustworthy and easy to use with an accent on data democratisation and decision enablement. Focus on evolving the data stack and development environment toward AI-optimised workflows, improving data quality, testing, lineage documentation, and operational runbooks.

Location: Warsaw, Masovia (Hybrid)

Salary: PLN 18'000 – 20'000 monthly base salary (employment contract, on request we can consider B2B too)

Company

hirify.global connects companies and workers through a platform built for flexible work, helping businesses plan smarter and supporting people in finding jobs that fit their lives.

What you will do

• Own the full data lifecycle: ingest data from source systems, build and maintain reliable pipelines into the Data Lake, and curate datasets.
• Deliver high-signal dashboards and reporting in Power BI, while partnering with stakeholders to refine requirements and improve discoverability and self-service through documentation and AI.
• Make data easy to use for everyone by reducing friction to get answers and maintaining a clear single source of truth for key metrics and definitions.
• Enable a “data in every decision” culture by embedding insights into planning and operations, and supporting and help shaping a chat-based interface that lets stakeholders query data in natural language with reliable, contextualised answers.
• Evolve the data stack and development environment toward AI-optimised workflows, including prompting patterns, automation, and review practices.
• Maintain strong operational hygiene through monitoring, alerting, incident response, and continuous improvement of engineering standards and practices.

Requirements

• Around 5 years of experience with strong fundamentals: SQL, data modelling, ETL/ELT patterns, and operating data pipelines in production.
• Databricks experience is a must (Spark/Delta, notebooks, jobs/workflows, Delta Lake concepts) and building/operating a Data Lake.
• Power BI knowledge is a must (data modelling, measures, performance considerations, and stakeholder-facing reporting).
• Strong engineering standards: CI/CD, testing strategies, observability, performance tuning, and production readiness for data pipelines.
• Experience owning data end-to-end: ingestion, transformations, data quality, and delivery to business-facing artifacts.
• Fluent English

Nice to have

• Interest in conversational data experiences (chat-based access to trusted metrics, definitions, and insights).
• AI-first development mindset: comfortable using AI tools to speed up delivery and strong judgment on validation, correctness, and safety.
• Clear communication with business stakeholders, dev teams, and clients, including translating needs into data products.

Culture & Benefits

• Hybrid working model (on average up to 1 or 2 days per week on-site).
• 26 days’ annual leave.
• Team events and company gatherings.
• 10% target bonus and ESOP eligibility.
• Agile, Collaborative, Empowering, Fair, and Passionate values.

Hiring process

• Prescreening: conversation with our internal recruiter.
• Technical interview.
• Hiring Manager Conversation: discussion with the VP Engineering and VP Product.