Senior Data Engineer (GCP)

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. Originally posted on Himalayas