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описание
Comm-IT provides data engineering and analytics services, delivering advanced data solutions for complex customer environments with a focus on Google Cloud Platform and modern GCP data technologies.
задачи
Design and develop scalable data solutions on GCP;
Lead the technical design and implementation of customer data projects;
Translate business and technical requirements into effective data architectures;
Build and maintain ETL/ELT pipelines, Data Lakes, Lakehouses, and cloud-based Data Warehouses;
Design data models and integration processes for Batch and real-time workloads;
Work with structured, semi-structured, and unstructured data;
Select technologies based on performance, scalability, security, and cost requirements;
Implement data quality, monitoring, governance, and orchestration processes;
Collaborate with Data Architects, Data Engineers, DevOps teams, analysts, and customer stakeholders;
Participate in developing analytics, AI, and ML solutions where relevant.
требования
At least 5 years of professional experience as a Data Engineer;
Hands-on experience developing data solutions on GCP;
Experience with data visualization tools such as Looker, Power BI, Tableau, or QuickSight;
Experience with data modeling, orchestration, performance optimization, and large-scale data processing;
Strong Python development skills, including building data pipelines and ETL/ELT processes;
High proficiency in SQL;
Experience designing and developing cloud-based Data Warehouses and Lakehouse solutions;
Experience with ETL/ELT and transformation tools such as dbt, Dataform, Rivery, or similar platforms;
Familiarity with CI/CD, Git, Infrastructure as Code, and production deployment practices;
Strong analytical and problem-solving skills with excellent attention to detail;
Ability to learn new technologies independently and work across multiple projects;
Strong experience with several GCP services, including BigQuery, Cloud Storage, Dataflow, Dataproc, Cloud Composer, Cloud Run, or Cloud Functions;
Fluent English;
Nice to have: Hands-on experience with AWS or Microsoft Azure data services, AWS Glue, Redshift, EMR, Kinesis, Azure Data Factory, Synapse, Databricks, real-time data processing and streaming architectures, Kafka or other event-driven platforms, AI and ML services such as Vertex AI, Gemini, BigQuery ML, SageMaker, Bedrock, or Azure Machine Learning, relevant GCP professional certifications, previous experience in consulting or customer-facing technology projects.