As a Data Architect, you will design and implement scalable, cloud-native data solutions that handle petabyte-scale datasets. You will lead architecture discussions, build robust data pipelines, and work closely with cross-functional teams to deliver enterprise-grade data platforms. Your work will directly support analytics, AI/ML, and real-time data processing needs across global clients.
Key Responsibilities:
- Translate complex data and analytics requirements into scalable technical architectures.
- Design and implement cloud-native architectures for real-time and batch data processing.
- Build and maintain large-scale data pipelines and frameworks using modern orchestration tools (e.g., Airflow, Oozie).
- Define strategies for data modeling, integration, metadata management, and governance.
- Optimize data systems for cost-efficiency, performance, and scalability.
- Leverage cloud services (AWS, Azure, GCP) including Azure Synapse, AWS Redshift, BigQuery, etc.
- Implement data governance frameworks covering quality, lineage, cataloging, and access control.
- Work with modern big data technologies (e.g., Spark, Kafka, Databricks, Snowflake, Hadoop).
- Collaborate with data engineers, analysts, DevOps, and business stakeholders.
- Evaluate and adopt emerging technologies to improve data architecture.
- Provide architectural guidance in cloud migration and modernization projects.
- Lead and mentor engineering teams and provide technical thought leadership.
Required Skills and Experience:
- Bachelor's or Master's in Computer Science, Engineering, or related field.
- 10+ years of experience in data architecture, engineering, or platform roles.
- 5+ years of experience with cloud data platforms (Azure, AWS, or GCP).
- Proven experience building scalable enterprise data platforms (data lakes/warehouses).
- Strong expertise in distributed computing, data modeling, and pipeline optimization.
- Proficiency in SQL and NoSQL databases (e.g., Snowflake, SQL Server, Cosmos DB, DynamoDB).
- Experience with data integration tools like Azure Data Factory, Talend, or Informatica.
- Hands-on experience with real-time streaming technologies (Kafka, Kinesis, Event Hub).
- Expertise in scripting/programming languages such as Python, Spark, Java, or Scala.
- Deep understanding of data governance, security, and regulatory compliance (GDPR, HIPAA, CCPA).
- Strong communication, presentation, and stakeholder management skills.
- Ability to lead multiple projects simultaneously in an agile environment.
