GCP Data Engineer

Job description

**Company Description** Tiger Analytics is a global consulting and services firm that helps organizations cut through uncertainty and execute confidently using Data and AI-led transformation. The company designs and operationalizes advanced Data & AI solutions that create measurable business value at scale, leveraging deep knowledge of value chains, agile operating models, and modern platforms. Tiger Analytics works closely with strategic hyperscaler partners to engineer cutting-edge solutions that go beyond standard playbooks. The team consists of 5000+ technologists and consultants collaborating across offices in the US, India, Canada, Mexico, UK, Spain, Singapore, and Australia. Applicants join a culture focused on reimagining what AI can achieve for some of the toughest real-world problems. **Role Description** The GCP Data Engineer is a full-time role based in Bengaluru South with a hybrid work arrangement, combining on-site collaboration with some work-from-home flexibility. The role involves designing, building, and maintaining scalable data pipelines and architectures on Google Cloud Platform to support analytics, AI, and business intelligence initiatives. Day-to-day tasks include ingesting and transforming data from multiple sources, optimizing data storage and processing, and ensuring data quality, security, and reliability across environments. The GCP Data Engineer partners with data scientists, analysts, and business stakeholders to understand requirements, translate them into robust technical solutions, and support deployment and performance tuning. The role also includes documenting data workflows, monitoring GCP resources, and contributing to continuous improvement of data engineering standards and best practices. **Qualifications** - Strong GCP data engineering skills, including experience with services such as BigQuery, Cloud Storage, Dataflow, Pub/Sub, and Cloud Composer. - Proficiency in programming and scripting for data engineering, ideally in Python and SQL, with experience in building ETL/ELT pipelines. - Solid understanding of data modeling, data warehousing concepts, and design of scalable data architectures and batch/streaming solutions. - Experience with modern data tools and frameworks (e.g., Apache Beam, Spark, Airflow) and version control systems such as Git. - Knowledge of cloud security, governance, and performance optimization practices in GCP, including IAM, monitoring, and cost management. - Ability to work closely with cross-functional teams, translate business needs into technical specifications, and communicate complex concepts clearly. - Bachelor’s or master’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience. - Prior experience in data engineering roles within analytics, consulting, or product organizations; exposure to AI/ML use cases is a plus.