Lead Software Engineer

Data Platform Architecture & Pipeline EngineeringDesign & Build: Develop robust, scalable, and automated Lambda/Kappa data pipelines for both batch and real-time streaming data using GCP Dataflow (Apache Beam) and Cloud Data Fusion.Data Warehousing: Optimize and manage enterprise data warehouses in Google BigQuery, ensuring efficient storage, partitioning, clustering, and query performance.Orchestration: Work with orchestration tools like Cloud Composer (Apache Airflow) to manage complex data workflows and dependencies.CI/CD & DevOps: Implement Infrastructure as Code (IaC) using tools like Terraform and maintain CI/CD pipelines for seamless data deployment.Business Intelligence & EnablementSemantic Modeling: Collaborate with analytics teams to model data and develop robust LookML models within Looker.Performance Tuning: Optimize Looker queries and BigQuery costs by implementing caching strategies, materialized views, and efficient BI Engine configurations.Data Governance & Quality (Preferred)Compliance & Security: Implement data governance frameworks on GCP using Dataplex, Cloud Data Loss Prevention (DLP), and IAM policies to ensure data privacy and compliance.Data Lineage & Cataloging: Establish and maintain data catalogs, metadata management, and end-to-end data lineage.Data Quality: Build automated testing frameworks to monitor data quality, anomalies, and pipeline health.Qualifications & SkillsGCP Expertise: Minimum of 3–5 years of hands-on experience building production-grade data solutions on Google Cloud Platform.Core Tools: Deep, practical knowledge of BigQuery (SQL optimization, slot management) and Dataflow (Apache Beam in Python or Java).Programming: Strong proficiency in Python, Java, or Scala, alongside expert-level SQL skills.Job SummaryJob number: CREQ261137Profession: OtherExperience: 5-7Years