Data Architect

Requirements:
Strong architecture and system-design mindset with the ability to balance long-term strategy and immediate business needs.
Ability to simplify complex data problems and design scalable, pragmatic solutions.
Strong ownership and ability to influence technical decisions across teams.
A hands-on technology leader who can design, review, and guide implementation rather than working purely at a conceptual level.
Strong focus on engineering excellence, reliability, security, and measurable business impact.
13-15 years of overall experience in data engineering, data architecture, or related areas, with significant experience in architecture and technical leadership.
Strong experience designing large-scale, distributed data platforms and enterprise data architectures.
Strong understanding of data modeling, data warehousing, data lakes, lakehouse architecture, and distributed data processing.
Hands-on experience with technologies such as Spark, Kafka, Airflow, Databricks, Snowflake, BigQuery, Redshift, or equivalent platforms.
Strong programming experience in Python, Java, or Scala.
Strong knowledge of SQL and database technologies, including relational and NoSQL databases.
Experience with cloud platforms, preferably AWS, with a strong understanding of cloud-native data services.
Experience designing real-time and batch data processing architectures.
Strong understanding of microservices, APIs, distributed systems, and event-driven architectures.
Experience with data governance, security, quality, lineage, metadata, and compliance.
Strong understanding of data architecture patterns and best practices for scalability, availability, performance, and cost optimization.
Experience working with CI/CD, DevOps, infrastructure automation, and observability for data platforms.
Excellent problem-solving, communication, stakeholder management, and technical leadership skills.
Good to Have:
Experience architecting data platforms for AI/ML and generative AI applications.
Knowledge of vector databases, RAG architectures, knowledge graphs, and AI data platforms.
Experience with Data Mesh, Data Fabric, or modern lakehouse architectures.
Experience with technologies such as Delta Lake, Iceberg, dbt, Kubernetes, Terraform, or equivalent.
Experience in building enterprise-scale platforms in a high-growth product/SaaS environment.
Prior experience leading architecture initiatives across multiple engineering teams.

Experience
12-16 yrs