Technical Lead

Job Title Lead Developer / Engineer Years of Experience 6 to 10 years Job Description We are seeking an experienced GCP Cloud Tech Lead Data Engineering to lead the design, development, and modernization of scalable, secure, and high-performance data platforms on Google Cloud In this role, you will: Provide technical guidance Define cloud data architecture Mentor engineers Ensure best practices across data engineering, analytics, and AI initiatives You will work closely with architects and business stakeholders to translate complex requirements into robust cloud-native data solutions Must-Have Skills SQL Python (Mandatory) Strong expertise in SQL and Python Advanced SQL for: Data modeling Transformations Performance tuning Analytics in BigQuery Strong Python proficiency with: OOP principles (encapsulation, inheritance, polymorphism, abstraction) SOLID principles Design patterns Data Engineering Pipelines Proven experience designing and building modular, scalable ETL/ELT pipelines Strong system design, troubleshooting, and performance tuning skills Experience working with distributed data systems GCP Cloud Expertise Hands-on experience with Google Cloud Platform (GCP) services: BigQuery Cloud Storage (GCS) Cloud Functions Cloud Run Cloud Composer Pub/Sub Strong understanding of event-driven and real-time architectures using Pub/Sub and Eventarc Integration APIs Experience integrating and consuming REST APIs for data ingestion and platform integration Data Governance Security Solid understanding of: Data governance Data quality Privacy Security best practices in cloud environments DevOps CI/CD Experience building and automating CI/CD pipelines Familiarity with Cloud Build (preferred) Collaboration Communication Excellent verbal and written communication skills Ability to explain complex technical concepts to non-technical stakeholders Strong collaboration with product, engineering, QA, DevOps, and compliance teams Good-to-Have Skills Experience with Dataform for SQL-based transformations Exposure to Dataflow (Apache Beam) for large-scale batch and streaming processing Knowledge of cloud cost optimization and performance tuning on GCP Experience with API testing tools (eg, Postman) Understanding of: Clean architecture Microservices Domain-driven design Experience building reusable frameworks, libraries, or accelerators Exposure to AI/ML pipeline orchestration Key Responsibilities Architecture Development Lead design and implementation of scalable ETL/ELT pipelines on GCP Develop high-performance SQL models and Python-based data applications Architect and maintain cloud-native solutions using: BigQuery, GCS, Cloud Functions, Cloud Run Cloud Composer, Pub/Sub, Eventarc, Dataform Real-Time Integration Define and implement event-driven, real-time data architectures Lead integration with external APIs and enterprise systems Governance Best Practices Establish standards for: Data quality Governance Lineage Security Compliance DevOps Performance Build and maintain CI/CD pipelines (Cloud Build) Ensure: Performance Scalability Reliability Cost efficiency Leadership Collaboration Provide technical leadership and mentorship Partner with cross-functional teams to deliver scalable solutions Maintain high-quality: Technical documentation Architecture diagrams Engineering standards Education Qualification Bachelor s or Master s degree in: Computer Science Information Systems Data Engineering Or a related field Certifications GCP Professional Data Engineer Certification (preferred) Snowflake Associate / Core certification Additional certifications (any one preferred): Databricks Snowflake Other cloud data platform certifications Shift Timing 12:00 PM 9:00 PM IST OR 2:00 PM 11:00 PM IST Location: DGS India - Bengaluru - Manyata N1 Block Brand: Merkle Time Type: Full time Contract Type: Permanent Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.