Middle+/Senior Data Engineer (Python)

instinctools is a software development company that provides custom software solutions for businesses of all sizes. Our team works closely with clients to understand their specific needs and provide personalized solutions that meet their business requirements. instinctools is looking for a Middle+/Senior Data Engineer (Python) for one of our clients. Location: remote Client: a global mobility and urban services platform that allows users to book rides or other services and negotiate the fare directly with the service provider. It offers a variety of services including ride-hailing, intercity travel, delivery, and task assistance, operating in over 700 cities across 47 countries and is the second most downloaded mobility app in the world. Duration of cooperation: 6-12 months+ Tasks: Data Engineering & Infrastructure (Core Focus): Design, develop, and maintain end-to-end data pipelines (ETL/ELT) from diverse source systems to the Data Warehouse. Build scalable and cost-efficient infrastructure for storing and processing large datasets within our cloud environment. Implement and advance systems for monitoring, alerting, and automated validation of data flows and Data Quality. Participate in system design and data architecture evolution, focusing on performance, resilience, and security. Proactively optimize existing data pipelines and DWH queries for efficiency and cost reduction. Collaboration & Documentation: Collaborate closely with Data Analysts to technically clarify requirements for data delivery and transformation logic. Conduct root cause analysis of data quality incidents and develop sustainable engineering solutions to prevent recurrence. Create and maintain technical documentation covering DWH schemas, pipeline architecture, and data lineage. Our expectations of the ideal candidate: Expert proficiency in Python 3.7+ for pipeline development and advanced level SQL. Deep understanding of multi-layered DWH architecture (e.g., Raw, ODS/Staging, Data Marts). Extensive experience building ETLs with Airflow 2. Excellent knowledge of OOP, design patterns, clean architecture. Professional experience with a major cloud data platform, specifically with Object Storage services (e.g., Google Cloud Storage, Amazon S3, or Azure Blob Storage). Experience working with a Cloud Data Warehouse (e.g., Google BigQuery, Snowflake, or Redshift). Mandatory experience with Git for version control and collaborative development. Nice-to-haves: Experience designing and working with high-load/low-latency data systems or message brokers (e.g., Kafka, PubSub). Professional proficiency in DevOps practices and CI/CD automation (e.g., GitHub Actions, GitLab CI). Experience with Infrastructure as Code (IaC), particularly Terraform. Understanding of and experience with containerization and orchestration (Docker, Kubernetes). Participating in testing, acceptance of developed functionality, and investigation of data quality incidents. Strong self-management: ability to work independently and meet deadlines. Proactive and ownership-driven mindset. Effective and clear communication, including in distributed teams. Collaborative, open to feedback, and focused on shared goals. Strong problem-solving skills, especially in ambiguous contexts. High attention to detail and code quality. Adaptability to shifting priorities and new technologies. English: Upper-Intermediate or higher. Working time zone: CET. We offer: Flexible working time. Professional and ambitious team. Learning opportunities, seminars and conferences, and time for exploring new technologies. Co-funding for language courses (English). We value diversity and encourage people of all backgrounds to apply. #J-18808-Ljbffr instinctools EE Labs