Key Responsibilities:

Design, build, and maintain scalable data pipelines and analytics solutions utilizing Google Cloud Platform (GCP) services. Develop and implement data processing architectures and frameworks to support business intelligence and analytics.

Experience & Qualifications:

Experience: Over 10 years of experience in data engineering or related fields. Minimum of 2 years in a Lead Data Engineer. At least 2 years of hands-on experience with the Google Cloud Platform (GCP) technology stack. Technical Skills: Strong proficiency with GCP services including BigQuery, BigTable, Dataflow, Dataprep, Pub/Sub, Cloud SQL, and Composer. Proficient in programming languages such as Python or Java. In-depth understanding of data modeling, data warehousing, ETL tools and best practices, and database design and optimization. Experience with both relational and NoSQL databases (e.g., MySQL, PostgreSQL, SQL Server, Oracle, Bigtable, Firestore, MongoDB, Cassandra). Familiarity with data security principles and best practices. Knowledge of Infrastructure as Code (IaC) tools such as Terraform and Ansible. Experience with test automation and observability tools including GCP Cloud's operations suite, ELK stack, Grafana, Prometheus. Certifications: GCP Professional Data Engineer certification is highly desirable.