Senior Data Engineer

Talan – Positive Innovation

Talan is an international consulting group specializing in innovation and business transformation through technology. With over 7,200 consultants in 21 countries and a turnover of €850M, we are committed to delivering impactful, future-ready solutions.

Talan at a Glance

Headquartered in Paris and operating globally, Talan combines technology, innovation, and empowerment to deliver measurable results for our clients. Over the past 22 years, we’ve built a strong presence in the IT and consulting landscape, and we’re on track to reach €1 billion in revenue this year.

Our Core Areas of Expertise

• Data & Technologies: We design and implement large-scale, end-to-end architecture and data solutions, including data integration, data science, visualization, Big Data, AI, and Generative AI.

• Cloud & Application Services: We integrate leading platforms such as SAP, Salesforce, Oracle, Microsoft, AWS, and IBM Maximo, helping clients transition to the cloud and improve operational efficiency.

• Management & Innovation Consulting: We lead business and digital transformation initiatives through project and change management best practices (PM, PMO, Agile, Scrum, Product Ownership), and support domains such as Supply Chain, Cybersecurity, and ESG/Low-Carbon strategies.

We work with major global clients across diverse sectors, including Transport & Logistics, Financial Services, Energy & Utilities, Retail, and Media & Telecommunications.

Data Engineering & Pipeline Development

• Design, build, and maintain scalable and reliable data pipelines (batch and streaming).

• Ingest and integrate data from multiple sources (SQL/NoSQL databases, APIs, files, cloud services).

• Develop and maintain efficient ETL/ELT processes and data workflows.

• Ensure data quality, integrity, and availability across the data lifecycle.

• Optimize data storage and processing for performance and cost efficiency.

Data Platform & Architecture

• Design and maintain modern data architectures (Data Lake, Data Warehouse, Lakehouse).

• Implement scalable data models to support analytics and operational use cases.

• Manage orchestration, scheduling, and monitoring of data pipelines.

• Maintain and improve cloud-based data infrastructure.

• Apply data governance practices, version control, and technical documentation standards.

AI/ML & Data Infrastructure Support

• Build and maintain data pipelines that support AI and Machine Learning use cases.

• Prepare curated datasets and feature-ready data for Data Science teams.

• Implement ingestion and processing pipelines for LLM-based applications.

• Manage embedding pipelines and integrations with vector databases.

• Support RAG architectures from a data engineering and infrastructure perspective.

Monitoring, Reliability & Performance

• Implement monitoring, alerting, and observability for data pipelines and workflows.

• Detect and resolve data quality issues, pipeline failures, and performance bottlenecks.

• Optimize queries, data models, and processing jobs to improve scalability and reliability.

Requirements

• Strong experience with Python focused on data processing and pipeline development.

• Advanced SQL skills and solid understanding of data modeling concepts.

• Hands-on experience with:

  • ETL/ELT frameworks

  • Workflow orchestration tools (e.g., Airflow, Prefect, Dagster, or similar)

  • Distributed data processing frameworks (e.g., Apache Spark or similar)

• Experience working with cloud platforms, especially:

  • Microsoft Azure (e.g., Data Factory, Synapse, Fabric, Azure AI Foundry)

  • Google Cloud (e.g., BigQuery, Dataflow, Cloud Composer, or similar services)

• Experience supporting LLM-based data infrastructure, including:

  • Vector databases

  • Embedding pipelines

  • Integration with frameworks such as LangChain (from a data engineering perspective)

• Familiarity with BI tools and supporting analytical data models (Power BI, Tableau, Qlik).

• Strong communication skills and ability to work in cross-functional teams.

• High level of English and Polish is a must.