As a leading provider of Human Resources consulting services in Transylvania, we deliver regional coverage and specialized expertise across four core areas: recruitment and selection, personnel leasing, assessment centers and HR consultancy. With a strong and consistent presence on the Romanian market, we continue to consolidate our position through a strategic commitment to continuous improvement and alignment with evolving business needs.
Our success is founded on the professionalism of our services, the multidisciplinary capabilities of our consulting team, and the long-standing partnerships we maintain with clients who rely on our support in navigating complex HR challenges.
We collaborate with organizations across a broad range of industries, including IT&C, automotive, outsourcing, pharmaceutical, banking, FMCG and others, building sustainable, long-term relationships that contribute to their organizational growth.
Guided by the principles of client orientation, teamwork, flexibility, excellence, dedication, and responsibility, we remain focused on delivering measurable value and consistently high-quality services to our partners.
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.
