Job Description

Design, develop, and maintain high-performance data pipelines using GCP services such as BigQuery, Dataflow, Pub/Sub, and Composer (Airflow). Design and develop Looker Dashboards, with apt security provisioning and drill down capabilities. Ensure data security, lineage, quality, and compliance across GCP data ecosystems through IAM, audit logging, data encryption, and schema management. Monitor, troubleshoot, and optimize pipeline and warehouse performance using GCP native tools such as Cloud Monitoring, Cloud Logging, and BigQuery Optimizer. Write SQL queries, dbt models, or Dataflow pipelines to transform raw data into analytics-ready datasets. Develop and optimize SQL queries and data transformation scripts for data warehousing and reporting purposes. Lead proof-of-concepts (POCs) and best practice implementations for modern data architecture, including data lakes and cloud-native data warehouses. Ensure data quality, governance, and security best practices across all layers of the data stack. Write clean, maintainable, and efficient code following best practices. Requirements Data Engineering: 8–12 years of experience in data engineering, with at least 3–5 years hands-on experience specifically in Google Cloud Platform (GCP) and BI tools like Looker. BigQuery (data modeling, optimization, security); Advanced SQL proficiency with complex data transformation, windowing functions, and analytical querying. Ability to design and develop modular, maintainable SQL models using dbt best practices. Basic to intermediate knowledge of Python for scripting and automation. Exposure to ETL and batch scheduling/ orchestration solutions Strong understanding of data architecture patterns: data lakes, cloud-native data warehouses, event-driven architectures. Experience with version control systems like Git and branching strategies. Looker: Hands on experience in Looker with design, development, configuration/ setup, dashboarding and reporting techniques. Experience building and maintaining LookML models, Explores, PDTs, and semantic layers. Understanding of security provisioning and access controls, performance tuning of dashboard/ reports based on large dataset, building drill down capabilities. Proven ability to design scalable, user-friendly dashboards and self-service analytics environments. Expertise in optimizing Looker performance: materialized views, query tuning, aggregate tables. Strong command over Row-Level Security, Access Filters, and permission sets in Looker to support enterprise-grade data governance. General: Experience with Agile delivery methodologies (e.g. Scrum, Kanban) Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment. Conduct regular workshops, demos and stakeholder reviews to showcase data solutions and capture feedback. Excellent communication and collaboration skills. Collaborate with development teams to streamline the software delivery process and improve system reliability. Mentor and upskill junior engineers and analysts on GCP tools, Looker modeling best practices, and advanced visualization techniques. Ability to translate business objectives into data solutions with a focus on delivering measurable business value. Flexible to work in shifts and provide on-call support, owning the smooth operation of applications and systems in a production environment.