Principal Data Infrastructure Engineer

As a Lead Data Engineer at Accordion, your role involves architecting and maintaining modern, scalable data platforms to drive analytics, AI, and decision-making for client organizations. You will work closely with client stakeholders to understand business challenges and translate them into actionable data architecture requirements and solution roadmaps. Your responsibilities will include leading the design of cloud-native data platform architectures, collaborating with cross-functional teams to define KPIs and data models, and developing and executing delivery plans within agreed timelines. Additionally, you will evaluate and implement data integration patterns, design AI-ready data infrastructure, and leverage AI tools to accelerate pipeline development and solution delivery. Key Responsibilities: - Partner with client stakeholders to understand business challenges and translate them into data architecture requirements and solution roadmaps. - Lead the design of cloud-native data platform architectures, including data lakes, lakehouses, and modern data warehouses. - Collaborate with business and technology teams to define KPIs, data models, and metrics frameworks aligned with client goals. - Develop and execute delivery plans ensuring high-quality output within agreed timelines. - Evaluate and lead the implementation of data integration patterns and real-time data processing. - Design and deploy MCP servers to expose data platform capabilities as tools for AI agents and workflows. - Conduct technical design reviews, architecture assessments, and knowledge transfer sessions for junior engineers. - Stay updated on emerging technologies, cloud platforms, AI tooling, and data ecosystem innovations to deliver forward-thinking solutions. Qualifications Required: - Undergraduate degree (B.E/B.Tech.) from a tier-1 or tier-2 institution. - 69 years of relevant experience in data engineering, data platform development, or cloud data architecture. - Strong SQL proficiency with experience in data modeling across relational and columnar databases. - Hands-on experience with cloud data platforms such as Azure Synapse Analytics, Databricks, Snowflake, etc. - Proficiency in cloud-native orchestration tools like Azure Data Factory, Databricks Workflows, etc. - Experience with MCP servers, AI tools, and BI tools is a plus. - Strong problem-solving mindset with the ability to drive innovation and lead technical discussions. Join Accordion to experience a culture of impact and excellence, where you will thrive in a high-growth environment with recognition cycles, diverse workstreams, and entrepreneurial freedom. Benefit from comprehensive health and security coverage, family support, empowering leave structures, and continuous growth opportunities in a transparent and supportive environment. Thrive at Accordion where your personal well-being and professional growth are prioritized. As a Lead Data Engineer at Accordion, your role involves architecting and maintaining modern, scalable data platforms to drive analytics, AI, and decision-making for client organizations. You will work closely with client stakeholders to understand business challenges and translate them into actionable data architecture requirements and solution roadmaps. Your responsibilities will include leading the design of cloud-native data platform architectures, collaborating with cross-functional teams to define KPIs and data models, and developing and executing delivery plans within agreed timelines. Additionally, you will evaluate and implement data integration patterns, design AI-ready data infrastructure, and leverage AI tools to accelerate pipeline development and solution delivery. Key Responsibilities: - Partner with client stakeholders to understand business challenges and translate them into data architecture requirements and solution roadmaps. - Lead the design of cloud-native data platform architectures, including data lakes, lakehouses, and modern data warehouses. - Collaborate with business and technology teams to define KPIs, data models, and metrics frameworks aligned with client goals. - Develop and execute delivery plans ensuring high-quality output within agreed timelines. - Evaluate and lead the implementation of data integration patterns and real-time data processing. - Design and deploy MCP servers to expose data platform capabilities as tools for AI agents and workflows. - Conduct technical design reviews, architecture assessments, and knowledge transfer sessions for junior engineers. - Stay updated on emerging technologies, cloud platforms, AI tooling, and data ecosystem innovations to deliver forward-thinking solutions. Qualifications Required: - Undergraduate degree (B.E/B.Tech.) from a tier-1 or tier-2 institution. - 69 years of relevant experience in data engineering, data platform development, or cloud data architecture. - Strong SQL proficiency with experience in data modeling across relational and columnar databases. -