Data Architect

We are looking for an experienced Data Architect to define and drive the data architecture strategy across the organization. The ideal candidate will have strong expertise in designing scalable, secure, and high-performance data platforms and will work closely with Engineering, Product, Data Science, and Business teams to translate business requirements into robust data solutions. This role requires a hands-on technology leader who can drive architecture decisions, establish data standards, mentor engineering teams, and build modern data platforms supporting analytics, AI/ML, and business applications.

Responsibilities:

• Define and own the enterprise data architecture strategy, principles, standards, and technology roadmap.
• Design scalable and highly available data platforms, data lakes, data warehouses, and lakehouse architectures.
• Develop architecture for batch and real-time data ingestion, processing, transformation, and integration.
• Evaluate and recommend appropriate data technologies, platforms, frameworks, and tools based on business and technical requirements.
• Design robust data models, including conceptual, logical, and physical data models for operational and analytical workloads.
• Drive implementation of ETL/ELT pipelines, data integration frameworks, and data quality solutions.
• Architect solutions across cloud data platforms such as AWS/Azure/GCP and modern data technologies.
• Define data architecture patterns for analytics, reporting, data science, AI/ML, and GenAI use cases.
• Establish standards for data governance, security, privacy, metadata management, data lineage, and access control.
• Work closely with Data Engineering, Data Science, Product, Application Engineering, and Business teams to ensure alignment between business objectives and data architecture.
• Identify opportunities to improve data performance, scalability, reliability, cost efficiency, and operational excellence.
• Lead architecture reviews and provide technical guidance for complex data engineering initiatives.
• Mentor senior engineers and architects and contribute to building a strong data engineering and architecture practice.
• Stay current with emerging technologies in cloud, distributed systems, data platforms, AI/ML, and GenAI and assess their applicability to the organization.

Requirements:

• 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.