Data Solutions Lead

We are seeking an experienced Data Solutions Lead to drive the architecture, design, and delivery of enterprise-scale data platforms and products. The ideal candidate will possess strong expertise in Data Architecture, Data Modelling, Snowflake, AWS Cloud, Data Governance, and Modern Data Platforms, with a proven track record of leading cross-functional teams and engaging with business stakeholders to deliver scalable, secure, and high-performing data solutions.

Key Responsibilities

• Lead the end-to-end design and delivery of enterprise data platforms, data products, and analytics solutions.
• Define and implement scalable data architectures using modern cloud-native technologies and best practices.
• Design conceptual, logical, and physical data models supporting operational, analytical, and reporting workloads.
• Architect and optimize Snowflake data warehouse solutions for performance, scalability, security, and cost efficiency.
• Design and implement cloud-based data solutions on AWS, leveraging services such as S3, Glue, Lambda, EMR, Redshift, IAM, and Lake Formation.
• Establish and enforce data governance, data quality, metadata management, lineage, and master data management frameworks.
• Collaborate with business stakeholders, product owners, architects, and engineering teams to translate business requirements into technical solutions.
• Drive data platform modernization initiatives, including data lake, lakehouse, and cloud migration programs.
• Define architecture standards, development frameworks, and best practices for data engineering and analytics teams.
• Lead solution design workshops, architecture reviews, and technical governance forums.
• Provide technical leadership, mentoring, and guidance to data engineers, architects, and analysts.
• Ensure compliance with security, privacy, regulatory, and organizational standards.

Required Skills & Experience

• 10+ years of experience in Data Engineering, Data Architecture, or Data Solutions delivery.
• Strong expertise in Snowflake Architecture, Data Warehousing, and Performance Optimization.
• Hands-on experience with AWS Cloud Services including S3, Glue, Redshift, Lambda, IAM, CloudWatch, and Lake Formation.
• Strong understanding of Data Modelling methodologies including Dimensional Modelling, Star Schema, Snowflake Schema, and Data Vault.
• Experience designing and implementing Enterprise Data Platforms, Data Lakes, and Lakehouse Architectures.
• Deep understanding of Data Governance, Data Quality, Metadata Management, Data Lineage, and Security frameworks.
• Strong proficiency in SQL and exposure to Python-based data processing frameworks.
• Experience with ETL/ELT design, integration patterns, and large-scale data migration initiatives.
• Strong stakeholder management, requirements gathering, and client engagement experience.
• Proven ability to lead architecture discussions and influence technical strategy.

Preferred Skills

• Experience with Data Mesh and Modern Data Product frameworks.
• Knowledge of Apache Spark, Databricks, or equivalent big data technologies.
• Familiarity with BI and Analytics platforms such as Power BI, Tableau, or QuickSight.
• Experience with DevOps, CI/CD, Infrastructure as Code (Terraform/CloudFormation), and Agile delivery models.
• Snowflake and AWS certifications preferred.