Data Architect / Lead

Job description

Accountabilities: Design, build, and maintain scalable data infrastructure and pipelines that support diverse business and analytics use cases, ensuring reliability, performance, and long-term maintainability. Own end-to-end data workflows, translating business requirements into efficient, production-grade data pipelines and data models. Enhance data observability, lineage tracking, monitoring, and alerting systems to proactively prevent incidents and improve data quality. Define, manage, and evolve data schemas, data models, and SLAs for critical datasets powering enterprise metrics and reporting. Implement best practices for data governance, security, storage, and compliance to ensure integrity and regulatory alignment. Lead technical evaluations of new tools and technologies to continuously improve the data ecosystem and engineering efficiency. Mentor and guide junior engineers while participating in code reviews to ensure high engineering standards and knowledge sharing. Requirements 10+ years of experience in data engineering, data architecture, or similar roles, with strong expertise in building large-scale data systems and pipelines. Strong proficiency in Python and SQL for data processing, transformation, and optimization. Hands-on experience with modern data orchestration and transformation tools such as Apache Airflow and dbt. Solid understanding of distributed data systems and cloud data platforms such as Amazon Web Services, Google Cloud, or Microsoft Azure. Strong expertise in data modeling, data warehousing, data governance, and data lifecycle management. Proven ability to troubleshoot complex data issues and optimize pipelines for performance and cost efficiency. Excellent communication and collaboration skills with experience working across cross-functional teams and stakeholder groups. Experience mentoring engineers and contributing to technical leadership within data teams. Benefits Competitive compensation aligned with senior-level data architecture expertise Fully remote work flexibility within India Opportunity to lead high-impact, enterprise-scale data architecture initiatives Exposure to modern data stack tools and cloud-native technologies Collaborative and innovation-driven engineering culture Strong focus on professional growth, mentorship, and technical leadership development Opportunity to influence data strategy and core business decision-making systems How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1 This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Data Architect / Lead in India. This is a senior technical leadership role focused on building, scaling, and governing enterprise-grade data infrastructure and pipelines within a modern data ecosystem. You will design robust data architectures that support analytics, data science, and business intelligence use cases across the organization. The role combines hands-on engineering with strategic ownership of data models, pipelines, and governance frameworks. You will play a key part in improving data reliability, observability, and performance at scale. Working in a highly collaborative environment, you will partner with data scientists, analysts, and engineers to translate business needs into efficient data solutions. The position also involves evaluating emerging technologies and driving continuous improvement of the data platform. This is a high-impact role with visibility across core business metrics and decision-making processes.