Anblicks
Overview
As a Principal Data & AI Solutions Engineer, you will lead the design, development, and delivery of advanced data and AI solutions across cloud platforms. You will serve as a trusted advisor to clients and internal teams, driving innovation, ensuring architectural integrity, and enabling scalable, secure, and high-performing systems. This role demands deep hands-on expertise in at least one modern Cloud Data & AI platform and the ability to translate complex business needs into actionable technical strategies.
Key Responsibilities
Client Engagement & Advisory
Engage directly with enterprise clients to understand business goals and translate them into technical solutions.
Serve as a strategic advisor to executive stakeholders, guiding architecture decisions and transformation roadmaps.
Architecture & Solution Design
Lead the design of scalable, extensible, and secure data and AI architectures using platforms such as Snowflake, Databricks, Azure, AWS, or GCP.
Decompose future-state goals into actionable execution plans and reference architectures.
Hands-On Technical Leadership
Demonstrate deep hands-on expertise in at least one Cloud Data & AI platform, including environment setup, solution engineering, performance optimization, and cost management.
Build and validate prototypes, frameworks, and accelerators to support solution delivery.
Innovation & Reusability
Partner with innovation teams to develop reusable assets, accelerators, and business point solutions across verticals such as Financial Services, Healthcare, Retail, and Travel & Hospitality.
Project & Team Leadership
Lead multiple projects simultaneously, providing technical oversight and mentoring to engineering teams.
Ensure alignment with data governance, security, and compliance standards.
Collaboration & Enablement
Collaborate with product, marketing, and sales teams to support go-to-market strategies, demos, workshops, and client onboarding.
Required Skills & Experience
10+ years of experience in Data Analytics, AI, and Cloud Architecture roles.
Deep hands-on expertise and end-to-end solutioning experience with at least one Cloud Data & AI platform (e.g., Snowflake, Databricks, Azure Synapse, AWS Redshift, GCP BigQuery).
Strong understanding of data warehousing, ML/AI engineering, MLOps/AIOps, ata integration and Data Governance.
Proficiency in SQL, Python, and data engineering tools for automation and transformation.
Experience with ETL/ELT pipelines, data modeling, and visualization tools (Power BI, Tableau, Looker).
Proven ability to lead cross-functional teams and manage complex technical projects.
Excellent communication skills, with the ability to present technical concepts to non-technical audiences.
Preferred Qualifications
Experience with cloud migration and modernization initiatives.
Familiarity with industry-specific data models and domain-driven design.
Experience with data governance, privacy, and security frameworks.