Senior Solutions Architect – Data Engineering

Senior Solutions Architect – Data Engineering Location: India - Remote Employment Type: Full-time About Us: Narwal is a high-growth global AI, Data, and Quality Engineering services and solutions company headquartered in Cincinnati, Ohio. With a Global Delivery Model spanning the United States and Canada, nearshore delivery in Mexico, a growing presence in the United Kingdom, and offshore development centres in India, Narwal partners with leading enterprises to modernize data platforms, enable AI-driven innovation, and deliver next-generation quality engineering. Recognized on the Inc. 5000 list of fastest-growing companies, Narwal has also been named Best IT Services Company, Best Data Technology Company, and Tricentis Partner of the Year, and is a Certified Great Place to Work. Why Narwal? Narwal is on an ambitious growth journey, and this is an opportunity to be part of the leadership team shaping that story. The Role: We are seeking a highly experienced Data Solution Architect to lead client-facing architecture, pre-sales solutioning, and technical design authority for our Data Practice. This role will act as the bridge between sales and delivery, ensuring that solutions are both technically sound and executable on a scale. You will partner closely with the Head of Data and Head of AI, who lead offshore delivery, while owning architecture strategy and client engagement in the US. This is a hands-on leadership role, requiring deep technical expertise, strong communication skills, and the ability to influence both clients and internal teams. Key Responsibilities: Client Engagement & Technical Leadership - Lead client discovery workshops and technical discussions - Translating business requirements into practical data solutions - Build trusted advisor relationships with client stakeholders - Present solutions to executive and technical audiences Presales & Solutioning - Partner with sales to shape deals and proposals - Lead RFP/RFI responses, solution design, and estimation - Develop POCs, demos, and reference architectures - Improve win rates through strong technical positioning Delivery Oversight (Design Authority) - Provide architecture oversight during delivery - Ensure alignment between design and execution - Resolve technical escalations and design challenges - Minimize rework through clear upfront architecture Solution Architecture Leadership - Own end-to-end data engineering project delivery across engagements - Define scalable, secure, and cost-effective solutions - Serve as the final authority on technical design decisions Cross-Functional Collaboration - Work closely with: - Head of Data on Execution & delivery - Head of AI on advanced analytics & AI integration - Sales team on pipeline and deal strategy - Act as the single point of accountability for technical integrity Practice Development - Contribute to data practice strategy and growth - Build reusable solution accelerators and frameworks - Mentor teams on modern data architecture patterns - Support expansion into AI, analytics, and platform engineering Required Qualifications Experience - 12–15+ years in data engineering, architecture, or analytics - 5+ years in solution architecture or consulting roles - Strong experience in client-facing roles (consulting/services) - Proven track record in presales and deal support Technical Expertise - Modern data platforms (e.g., Snowflake, Databricks, BigQuery) - Cloud ecosystems (e.g., AWS, Azure, GCP) - Data engineering (ETL/ELT, pipelines, orchestration) - Data warehousing, data lakes and Lakehouse architecture - APIs, integrations, and real-time data processing - Data governance, security, and compliance Soft Skills - Strong executive communication and presentation skills - Ability to simplify complex technical concepts - High ownership and decision-making capability - Experience working with global/offshore teams - Strong problem-solving and critical thinking skills Preferred Qualifications - Experience in AI/ML integration with data platforms - Background in consulting or professional services firms - Exposure to multiple industries (finance, healthcare, retail, etc.) - Experience building or scaling data practice