• Analyze existing data import processes in an SQL-based data warehouse. • Design an automated import tool to support and automate ETL processes. • Develop a concept for automatic detection of data structures and data types, optionally using AI-based methods. • Conduct a market and tool analysis of existing solutions for data integration and provisioning as part of a make-or-buy assessment. • Evaluate the developed concept in terms of degree of automation, maintainability, and extensibility. • Document and present the results of your bachelor's thesis.

• Diseñar, desarrollar y mantener canalizaciones de datos (ETL/ELT) utilizando Python y SQL, bajo la Arquitectura Medallion, asegurando la transformación, limpieza y estructuración de los datos en Google Cloud Platform (GCP). • Diseñar modelos de datos relacionados y optimizar las consultas SQL para garantizar un procesamiento eficiente, escalable y de alto rendimiento, optimizando el uso de la infraestructura. • Desarrollar y mantener paneles e indicadores en Looker Studio y Grafana, facilitando la visualización de métricas clave para equipos de Producto, Negocio y Análisis. • Implementar prácticas de gobernanza, seguridad y automatización de datos a través de herramientas DevOps, asegurando el cumplimiento de los estándares de seguridad de la información e impulsando el uso de API e ingeniería de indicaciones para optimizar procesos.

Role Description This is a hands-on senior engineering role, not an architecture-only seat and not a support function. You’ll be responsible for technical direction, platform design and architectural decision-making. You'll design and build greenfield data platforms, real-time pipelines, and data products for clients who are serious about using data properly. You’ll work in small, high-calibre teams and operate close to both the problem and the client. If you enjoy solving hard data problems, shaping modern architectures (data mesh, data products, contracts), and delivering real outcomes — this is your lane. What You’ll Be Doing - Lead Platform & Architecture Design - Own the end-to-end architecture of modern, cloud-native data platforms - Design scalable data ecosystems using data mesh, data products, and data contracts - Make high-impact architectural decisions across ingestion, storage, processing, and access layers - Ensure platforms are secure, compliant, and production-grade by design - Build Modern Data Platforms - Design and deliver cloud-native data platforms using Databricks, Snowflake, AWS, and GCP - Apply modern architectural patterns: data mesh, data products, and data contracts - Integrate deeply with client systems to enable scalable, consumer-oriented data access - Develop High-Performance Pipelines - Build and optimise batch and real-time pipelines - Work with streaming and event-driven tech such as Kafka, Flink, Kinesis, Pub/Sub - Orchestrate workflows using Airflow, Dataflow, Glue - Work at Scale - Process and transform large datasets using Spark and Flink - Design systems that perform in production - not just on paper - Own Data Storage & Performance - Work across relational, NoSQL, and analytical stores (Postgres, BigQuery, Snowflake, Cassandra, MongoDB) - Optimise storage formats and access patterns (Parquet, Delta, ORC, Avro) - Cloud, Security & Governance - Implement secure, compliant data solutions with security by design - Embed governance without killing developer velocity - Consult and Influence - Work directly with clients to understand problems and shape solutions - Translate business needs into pragmatic engineering decisions - Act as a trusted technical advisor, not just an order taker - Technical Leadership & Quality - Set engineering standards, patterns, and best practices across teams - Review designs and code, providing clear technical direction and mentorship - Raise the bar on data quality, testing, observability, and operational excellence Qualifications - Strong Python and SQL - Deep experience with Spark and modern data platforms (Databricks / Snowflake) - Solid grasp of cloud data services (AWS or GCP) - Demonstrated ownership of large-scale data platform architectures - Strong data modelling skills and architectural decision-making ability - Comfortable balancing trade-offs between performance, cost, and complexity - Built and operated large-scale data pipelines in production - Strong data modelling capability and architectural judgement - Comfortable with multiple storage technologies and formats - Infrastructure-as-code experience (Terraform, Pulumi) - CI/CD pipelines using tools like GitHub Actions, ArgoCD - Data testing and quality frameworks (dbt, Great Expectations, Soda) - Experience in consulting or professional services environments - Strong consulting instincts — able to challenge assumptions and guide clients toward better outcomes - Comfortable mentoring senior engineers and influencing technical culture Benefits - You’ll work on interesting, high-impact problems - You’ll build modern platforms, not maintain legacy mess - You’ll be surrounded by senior engineers who actually know their craft - You’ll have autonomy, influence, and room to grow

Role Description - Work closely with technical leads and client teams to fully demonstrate the benefits of GCP technology. - As Google Cloud Platform (GCP) data migration engineer, responsible for overseeing the migration of data from various sources to Google Cloud Platform. - This role involves: - Analyzing existing data structures. - Designing migration strategies. - Implementing data migration processes. - Ensuring data integrity and security throughout the migration process. - Providing technical guidance and support to stakeholders. - Optimizing data migration processes for efficiency and scalability. - Documenting migration procedures and best practices. - Define and implement cloud-based solutions in line with industry best practices and enterprise architecture guidelines. Qualifications - Strong technical skills in GCP services, data migration tools, and new database technologies. - Experience with scripting languages. - Excellent problem-solving, communication, and collaboration abilities. - Database experience with either RDBM or NOSQL. - Technical writing experience in preparing and presenting technical material to a variety of audiences. - Experience in working in, and with, Agile delivery teams. Requirements - GCP experience. - Experience working on enterprise-level migration projects. - Experience in large-scale, secure, and high availability solutions in cloud environments such as Google Cloud (GCP). - Strong experience in Data Engineering, Data modeling, DBT is preferred. Qualities We Look For - Passionate about delivering high-quality commercial software products and platforms to market. - Team player; enjoy working with each other and clients. - Strong understanding of modern software engineering processes. - Client-focused and passionate about delivering business value. - Able to communicate clearly and efficiently with a variety of audiences including developers, clients, customers, partners, and executives. - Flexible and willing to use the right technology for each problem in the context of timelines and business goals. - Ability to complete the job regardless of the circumstance.