Regular Data Engineer

2 weeks ago

Bucharest, Bucureşti, Romania Luxoft Full time €30,000 - €60,000 per year

Project description

Join our Development Center and become a member of our open-minded, progressive and professional team. You will have a chance to grow your technical and soft skills, and build a thorough expertise of the industry of our client. In this role you will be working on projects for one our world famous clients, a large international investment bank.

On top of attractive salary and benefits package, Luxoft will invest into your professional training, and allow you to grow your professional career.

Responsibilities

  • Key Responsibilities:
  • Solution Design: Architect data pipelines down to the low-level elements, ensuring clarity and precision in implementation.
  • Data Sourcing: Extract data from diverse repositories including relational
  • databases (Oracle, PostgreSQL), NoSQL stores, file systems, and other
  • structured/unstructured sources.
  • Data Transformation: Design and implement ETL/ELT workflows to standardize and cleanse data using best practices in data engineering.
  • Pipeline Development: Build scalable, fault-tolerant data pipelines that support batch and streaming use cases.
  • Cloud data processing: Load transformed data into GCP destinations such as BigQuery or Cloud Storage using tools like Dataproc, Dataflow, and other GCPnative services.
  • Workflow Orchestration: Design and manage workflows using orchestration tools such as Apache Airflow or Cloud Composer.
  • Data Format Expertise: Work with various data formats including JSON, AVRO, Parquet, CSV, and others.
  • Optimization & Monitoring: Ensure performance, reliability, and cost-efficiency of data pipelines through continuous monitoring and tuning.
  • Collaboration: Work closely with data architects, analysts, and business
  • stakeholders to understand data requirements and deliver high-quality solutions.

Skills

Must have

  • Required Skills & Experience:
  • Experience in data engineering across hybrid environments (on-premise and cloud).
  • Proficiency in SQL and Python or Java/Scala.
  • Hands-on experience with ETL/ELT tools and frameworks.
  • Good understanding of GCP data services: BigQuery, Dataproc, Dataflow, Cloud Storage.
  • Familiarity with data modeling, schema design, and metadata management.
  • Knowledge of data governance, security, and compliance best practices.

Nice to have

  • Preferred Qualifications:
  • GCP certification (e.g., Professional Data Engineer) is a major plus
  • Experience with CI/CD for data pipelines.
  • Exposure to containerization and Kubernetes.
  • Familiarity with data cataloging tools / metadata management
  • Experience with Big Data technologies

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