Data Engineer Solution Architect

SRM Digital LLC is seeking an experienced Data Architect to design and lead the implementation of modern data platforms and analytics ecosystems. The role involves defining scalable data solutions, working closely with clients and internal teams, and supporting pre-sales initiatives.

Responsibilities:

• Design and implement modern data architectures, including lakehouse and cloud data warehouse solutions using Databricks and Snowflake
• Define end-to-end data platform architecture covering data ingestion, processing, storage, governance, and analytics layers
• Architect and optimize data platforms across AWS, Azure, and GCP cloud environments
• Lead the development of scalable ETL/ELT pipelines using technologies such as Spark, Python, SQL, and orchestration tools
• Establish standards for data modeling, data quality, security, and governance frameworks
• Engage with clients during pre-sales and solution discovery, providing architecture guidance and participating in technical workshops
• Collaborate with sales teams to create solution proposals, architecture diagrams, and effort estimates for client opportunities
• Provide technical leadership and architecture governance to engineering teams throughout the project lifecycle

Requirements:

• 10+ years of experience in data engineering, analytics platforms, or enterprise data architecture
• Strong expertise in Databricks (Spark, Delta Lake) and Snowflake data platform architecture
• Hands-on experience across AWS, Azure, and GCP cloud ecosystems for building scalable data platforms
• Proficiency in data pipeline development using Python, Spark, SQL, and orchestration tools such as Airflow or similar
• Strong knowledge of data modeling techniques (dimensional modeling, normalized models, data vault)
• Experience designing real-time and batch data processing architectures, including streaming and CDC pipelines
• Ability to conduct client workshops, architecture discussions, and technical presentations during pre-sales engagements
• Excellent communication and stakeholder management skills, with the ability to translate business needs into technical solutions
• Experience building data accelerators or reusable platform frameworks
• Exposure to AI/ML data pipelines and MLOps architectures
• Certifications in Databricks, Snowflake, AWS, Azure, or GCP at Professional category