Senior Data Engineer (GCP)

Stack

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

• ▹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.
• ▹Ability to learn new technologies independently and work across multiple projects.
• ▹Strong experience with several GCP services: 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.
• ▹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.

Soft skills