Top Data Engineer Jobs in Bucharest

As a Software Engineer on the data platform team, you'll automate data platform operations, write Python code, and collaborate on solutions within a distributed team.

Lead and deliver end-to-end corporate data pipelines and analytical datasets, ensuring reliability, scalability, data quality, lineage, and governance. Provide hands-on technical leadership, design large-scale data processing solutions, coach data engineers, collaborate with business stakeholders across group functions, and drive enterprise data standards and AI-ready practices to support corporate reporting, KPIs, and regulatory needs.

Join Zencore as a Senior Data Engineer, leveraging Google Cloud expertise and technology strategies to assist clients with data and application modernization.

Build and operate shared AI platform infrastructure for LLM applications, agents, RAG, tool calling, and AI workflows. Develop data and knowledge pipelines, secure enterprise integrations, reusable frameworks, deployment and observability standards, and developer tooling. Take AI systems from experimentation to reliable production while ensuring security, privacy, governance, scalability, quality, and cost efficiency. Collaborate across Engineering, Product, and IT to establish practical AI platform patterns and guardrails.

Design and scale mission-critical market data services for stocks, options, crypto, and foreign exchange. Responsibilities include architecting backend systems and APIs, maintaining software quality and test coverage, participating in code reviews, and troubleshooting incidents and bugs. The role uses Go and Python with REST, gRPC, WebSockets, SSE, Docker, Kubernetes, Google Cloud, BigTable, Prometheus, Grafana, and ELK.

Design, build, and scale high-performance data pipelines and infrastructure (ingestion, transformation, storage, modeling, serving) using ClickHouse, Postgres, Python and dbt. Manage data quality, reliability, and observability at terabyte and 500M+ address scale, collaborate with researchers and product, mentor engineers, and leverage AI tools to accelerate work.

Own and evolve the core data platform: warehouse design, dbt transformations, and production AWS pipelines. Refactor and harden API-driven data flows, ensure observability and testing, partner with backend and product teams, and contribute to data-aware backend features to deliver reliable, product-focused data.

As a Senior Software Engineer, you'll design and build scalable market data systems, improve API architecture, and enhance overall system performance, contributing to Alpaca's infrastructure for trading financial assets.

Seeking a Senior Data Support Engineer with 5-6 years of experience in Data Engineering, specifically utilizing Snowflake, Python, SQL, and AWS for data manipulation, warehousing, and testing processes.

Maintain and scale production data ingestion pipelines processing billions of events, support and optimize complex ETL and streaming workflows, develop platform tools and ML/streaming initiatives, ensure reliability/observability, and assist data scientists and analysts with production workloads.

Design and implement scalable Azure data platforms, develop data pipelines, and support clients with data modernization and governance practices.

Design and build highly scalable, low-latency market data systems and APIs. Implement backend services, influence architecture, maintain test coverage, participate in code reviews, troubleshoot incidents, and occasionally be on-call. Work spans streaming and historical market data endpoints and developer-focused API improvements.

Design, build, and operate Azure-based data platform environments and lead migrations to Azure/Databricks/Microsoft Fabric. Implement IaC (Terraform), Kubernetes platform operations, CI/CD automation, security and governance controls, monitoring/observability, and cost/performance optimizations. Collaborate with data engineers, architects, and stakeholders and produce technical documentation while providing technical leadership during the migration.

Conduct 60-minute technical interviews for senior data engineering candidates, evaluate cloud-based data platform architecture, ETL/ELT pipelines, distributed processing, security, data modelling, and communication. Complete scorecards, provide hiring recommendations, and collaborate with recruiters to improve assessments.

Design and maintain data infrastructure, build pipelines for data collection, ensure data quality, and collaborate with stakeholders on data requirements.