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Data Engineer - 20180

Veritaz AB · Stockholm · publicerad 4 dagar sedan

SeniorEngelska

Ort
Stockholm
Sista ansökningsdag
20 nov.
Publicerad
21 okt.
Arbetsform
På plats
Anställning
Tillsvidare (enligt annons)
Källa
Platsbanken
Medianlön för yrkesgruppen (2025): 49 500 kr/månSe lönestatistik →
Stockholm
Stockholm
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Om tjänsten

Veritaz is a leading IT staffing solutions provider in Sweden, committed to advancing individual careers and aiding employers in ensuring the perfect talent fit. With a proven track record of successful partnerships with top companies, we have rapidly grown our presence in the USA, Europe, and Sweden as a dependable and trusted resource within the IT industry. Job Overview Role Summary An experienced Senior Data Engineer is needed for a consulting assignment focused on developing and enhancing scalable data solutions for analytics, reporting, and decision support. Key Responsibilities Design, develop, deploy, and maintain robust data pipelines and analytical data models. Work across the complete data flow, including ingestion, transformation, modelling, data quality assurance, and production operations. Ensure data solutions meet requirements for performance, scalability, cost efficiency, and operational reliability. Develop production-ready data solutions using Python and SQL. Implement automated deployments and CI/CD workflows. Use Infrastructure as Code practices to provision and manage platform components. Collaborate with analytical and technical stakeholders on technical decisions, solution design, and delivery. Optimise data solutions for query performance, platform cost, and maintainability. Contribute to testing, monitoring, data quality, observability, and reliable operation of the data platform.

Technical Stack & Requirements Cloud platform: Google Cloud Platform (GCP) and BigQuery. Data transformation and modelling: dbt, SQL, and analytical data modelling. Programming: Python; Node.js and TypeScript are advantageous. Infrastructure and delivery: Terraform, Infrastructure as Code, GitHub Actions, CI/CD, and automated deployments. Integration and streaming: Kafka, Google Pub/Sub, and REST APIs are advantageous. Analytics and visualisation: Looker and LookML are advantageous. Operational capabilities: data quality, testing, monitoring, metadata, data lineage, and observability.

Qualifications & Experience You have substantial hands-on experience with GCP and BigQuery, very strong SQL skills, and solid experience using dbt. You have worked with data modelling for analytical use cases and have experience implementing CI/CD pipelines and automated deployments. Experience with Infrastructure as Code, preferably Terraform, and Python-based production data solutions is required. You should have a strong understanding of data quality, testing, monitoring, and operational reliability, as well as experience optimising data solutions for performance and cost. Experience working with large and complex data platforms is advantageous. The role requires the ability to work independently and systematically, analyse complex technical challenges, and take solutions through to production.

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