Description
We are looking for an experienced Senior Data Engineer to join a growing Data Engineering and Analytics department. In this role, you will design and develop advanced data solutions for complex customer environments, with a strong focus on Google Cloud Platform and modern GCP data technologies. You will work across the full data lifecycle- from architecture and data modeling to pipeline development, data platforms, analytics, and production deployment.
Key Responsibilities:
- Design and develop scalable data solutions on GCP.
- Lead the technical design and implementation of customer data projects.
- Understand business and technical requirements and translate them 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 the appropriate technologies based on performance, scalability, security, and cost requirements.
- Implement data quality, monitoring, governance, and orchestration processes.
- Work closely with Data Architects, Data Engineers, DevOps teams, analysts, and customer stakeholders.
- Participate in the development of analytics, AI, and ML solutions where relevant.
Requirements
Requirements:
- At least 5 years of professional experience as a Data Engineer – mandatory.
- Proven hands-on experience developing data solutions on GCP – mandatory.
- 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 – mandatory.
- 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 of the following GCP services: BigQuery, Cloud Storage, Dataflow, Dataproc, Cloud Composer, Cloud Run or Cloud Functions
- Fluent English.
Advantages
- Hands-on experience with AWS or Microsoft Azure data services.
- Experience with services such as AWS Glue, Redshift, EMR, Kinesis, Azure Data Factory, Synapse, or Databricks.
- Experience with real-time data processing and streaming architectures.
- Experience with Kafka or other event-driven platforms.
- Knowledge of AI and ML services such as Vertex AI, Gemini, BigQuery ML, SageMaker, Bedrock, or Azure Machine Learning.
- Relevant GCP professional certifications.
- Previous experience working in consulting or customer-facing technology projects.
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