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Regular Data Engineer

Sales Consulting
București, Bucharest, ROHybrid6mo ago

About the role

The role involves sourcing data from multiple systems, optimizing workflows and collaborating with architects and analysts to deliver clean, well-structured datasets.

Required Skills & Experience:

• 3+ years of 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:

• GCP certification (e.g., Professional Data Engineer) is a major plus.

• Experience with Big Data technologies.

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.

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