Lead Data Architect

Data Architect - Data & Analytics Delivery Practice Lead Fulltime Bengaluru/Coimbatore About the Role: We are seeking a highly skilled and results-driven Data & Analytics Delivery Practice Lead to lead our end-to-end data engineering, Big Data, Streaming and business intelligence (BI) solutions. This is a key leadership role for someone who thrives on building scalable, cloud-agnostic data solutions and driving measurable impact through data analytics. You will be responsible for managing a high-performing data team of 20+ members across onsite and offshore locations, primarily working on any Big Data, streaming Platforms Databricks, Snowflake, Redshift, Spark, Kafka, SQL Server, PostgreSQL on any Cloud ( AWS/Azure/GCP). Your expertise in Python, cloud infrastructure, and data architecture will be instrumental in creating intelligent and efficient data pipelines and products. In addition to delivery excellence, you will serve as the primary customer contact for ongoing engagements and play an active role in pre-sales efforts—participating in prospect calls and leading proposal creation with an exceptional success rate. Key Responsibilities: Team Leadership and Development: Lead, mentor, and develop a high-performing global team of 20+ data professionals across onshore and offshore locations. Foster a culture of accountability, innovation, and continuous learning within the data team. Establish career development plans and performance metrics to drive individual and team growth that aligns with organizational KPIs. Align team structure and skill sets with evolving business and technology needs. Delivery & Customer Focus: Serve as the primary point of contact for customers, ensuring successful delivery of data and analytics solutions. Translate complex customer requirements into scalable, high-impact data solutions. Maintain a strong focus on stakeholder engagement and satisfaction, ensuring delivery meets or exceeds expectations. Drive pre-sales activities, including client discovery calls and proposal development, maintaining close to 100% win rate. Technology & Market Adaptation: Architect and implement scalable, cloud-agnostic data solutions using technologies such as Big Data, streaming Platforms Databricks, Snowflake, Redshift, Spark, Kafka, SQL Server, PostgreSQL on any Cloud ( AWS/Azure/GCP) Stay ahead of technology trends in data engineering, cloud computing, and big data platforms to ensure competitive offerings. Evaluate and adopt emerging tools and frameworks that enhance productivity, performance, and innovation. Cross-Functional Collaboration with Global Teams: Collaborate closely with platform engineering, BI, and AI/ML teams to deliver integrated, end-to-end data solutions. Act as a bridge between technical and non-technical stakeholders, translating business needs into technical execution. Promote knowledge sharing and alignment across functional and geographical team boundaries. Process Improvement and Reporting: Define and continuously refine best practices in Technology frameworks and operational processes. Drive improvements in data quality, performance, and governance across the data lifecycle. Track team utilization and proactively forecast upcoming bench time, ensuring maximum billing efficiency and planning for resource allocation. Achieve and maintain 100% billing utilization by aligning team capacity with project demands. Generate and share regular utilization and billing reports with the leadership team to inform resourcing and financial strategies. Lead initiatives to automate and streamline data processes, reducing manual effort and increasing delivery speed. Required Skills and Qualifications: 10+ years of experience in Data Engineering and Analytics, with at least 3–5 years in a leadership role. Proven experience managing global teams, both onsite and offshore. Strong hands-on technical background in Big Data, streaming Platforms, Databricks, Snowflake, Redshift, Spark, Kafka, SQL Server, PostgreSQL on any Cloud ( AWS/Azure/GCP), and modern BI tools. Demonstrated ability to design and scale data pipelines and architectures in large, complex environments. Excellent soft skills including leadership, client communication, and stakeholder management. A successful track record of pre-sales engagement and proposal development with high closure rates. Experience working across cross-functional teams including platform and AI/ML engineering. Strong problem-solving mindset with the ability to think strategically and execute tactically. Preferred Qualifications: Master’s or Bachelor’s degree in Computer Science, Data Science, Engineering, or related field. Experience working in consulting or services-based environments. Familiarity with governance, data security, and compliance best practices. Exposure to modern data stack tools like dbt, Airflow, and Kafka.