Data Engineer, Communications Intelligence & Insights

Our requirements

• Strong experience in data engineering, with a track record of designing, building and maintaining reliable production-grade data pipelines and platforms.
• Advanced SQL skills and strong experience in relational database environments, including data transformation, modelling, optimisation and the creation of data structures for downstream analytics and reporting.
• Strong Python development capability, including writing clean, readable and object-oriented code, working with pandas and developing concurrent or scalable data-processing workflows.
• Hands-on experience with APIs, data integrations and ETL/ELT architectures, with the ability to bring together structured and semi-structured data from multiple sources.
• Experience working within cloud-based data environments, ideally Microsoft Azure, including cloud compute, managed databases, object storage and enterprise data-processing services.
• Strong software-engineering discipline, including experience designing and writing automated unit, integration and regression tests in Python, ideally using pytest.
• A strong understanding of secure engineering practices, including database security, firewalls and secure secrets and credential management using tools such as Azure Key Vault.
• Experience with Git-based engineering workflows and CI/CD environments, ideally including GitHub and Azure DevOps, with an appreciation for structured branching, code governance and multi-developer environments.
• Familiarity with Infrastructure-as-Code, ideally Terraform or Terragrunt, and the ability to safely manage or update environment variables, configuration and access controls within established infrastructure frameworks.
• Experience or strong interest in AI-enabled data engineering, including exposure to large language models, prompt-based workflows, automated enrichment or the integration of AI services into production data pipelines.
• Strong analytical, troubleshooting and technical-planning skills, with the ability to diagnose complex data and performance issues, scope engineering work effectively and build scalable solutions rather than short-term fixes.
• A collaborative and disciplined approach to engineering, comfortable working across multiple projects with analysts, engineers, product teams and business stakeholders while maintaining strong documentation, continuous improvement and adherence to agreed technical standards.

Your responsibilities

• Build, develop and maintain Burson’s core data platform and pipelines, supporting scalable ingestion, transformation, storage and delivery of intelligence data across the EMEA Hub.
• Design and manage robust ingestion pipelines for media monitoring, social listening, APIs, internal datasets and third-party research and analytics sources.
• Develop transformation and data-modelling layers using SQL and Python, creating both standardised central data models and bespoke client datasets that support downstream reporting, including Power BI.
• Design and deliver client-specific data engineering solutions, developing custom pipelines, integrations and datasets where off-the-shelf technology does not meet complex or specialist requirements.
• Optimise the performance, scalability and reliability of data systems, identifying bottlenecks, resolving data-quality issues and continuously improving pipeline efficiency.
• Develop reusable engineering frameworks, templates and components that enable the Hub to scale solutions consistently across clients, markets and use cases.
• Contribute to AI-enabled workflows, embedding language models into data pipelines to automate content analysis, classification, tagging, summarisation, relevance, sentiment and other enrichment processes.
• Develop and refine prompting frameworks and AI-processing workflows, including monitoring and optimising token usage to ensure effective, efficient and commercially sustainable AI enrichment at scale.
• Partner with analysts, product teams and communications specialists to translate approved business and reporting requirements into clearly defined technical solutions and identify appropriate opportunities for AI and automation.
• Work within a structured Agile and ticket-driven engineering environment, contributing to sprint planning, daily stand-ups and technical design discussions while delivering against agreed functional specifications and architectural standards.
• Maintain strong engineering governance and security standards, including consistent code practices, Git workflows, secure credential management, database security and adherence to agreed directory and repository structures.
• Own high-quality technical documentation, maintaining clear technical guides, markdown documentation, database schemas and system records while contributing to planned refactoring and technical-debt reduction without disrupting production services.

About the project

What we offer

• The opportunity to work at one of the largest and most awarded PR agencies in Poland and worldwide
• A hybrid working model
• Access to a suite of generative AI tools
• Fully funded private healthcare package for employees
• A benefits platform with a flexible cafeteria system (including Medicover Sport)
• A clear career path and opportunities for professional development through both global and local training programs.
• EAP

Benefits

• sharing the costs of sports activities
• private medical care
• flexible working time
• fruits
• integration events
• coffee / tea
• employee referral program
• extra leave