The Associate Data Architect will be responsible for designing and implementing scalable, high-performance data architectures across modern data platforms.
This role requires deep expertise in data modeling, schema design, database optimization, and the development of enterprise-level data solutions.
The architect will work across cloud and big-data environments, ensuring strong data governance, quality, lineage, security, and compliance. Hands-on coding experience and the ability to build robust data solutions from the ground up are essential.
Key Responsibilities
- Design and implement scalable enterprise data architectures supporting analytics, warehousing, and operational workloads.
- Develop logical and physical data models, schemas, and optimized database structures for large-scale systems.
- Work with relational and NoSQL databases, ensuring high availability, performance, and reliability.
- Architect cloud-native data solutions using platforms such as Azure, Databricks, Snowflake, and Redshift.
- Implement big-data processing frameworks (e.g., Spark) for distributed computing and large-volume data pipelines.
- Build and optimize ETL and ELT workflows using modern cloud-based data engineering tools.
- Establish and maintain data governance best practices including data lineage, metadata management, and data quality.
- Ensure data security standards, encryption, and regulatory compliance throughout all environments.
- Collaborate with cross-functional teams including engineering, data governance, analytics, and security.
- Provide hands-on development of data solutions, including coding, testing, and performance tuning.
- Recommend improvements to data architecture, tools, and processes to support evolving business needs.
Required Qualifications
- Minimum 15+ years of experience in data architecture, data engineering, or related technical roles.
- Extensive experience designing and implementing scalable data architectures.
- Strong expertise in data modeling, schema design, and database optimization.
- Deep knowledge of RDBMS and NoSQL systems, including modern cloud-based and on-premise environments.
- Hands-on experience with data warehousing platforms such as Databricks, Snowflake, or Redshift.
- Proficiency with big-data technologies, especially Apache Spark.
- Strong experience with cloud environments, particularly Azure, including cloud-native data services.
- Expertise in ETL/ELT development and modern data pipeline tools.
- Strong understanding of data governance practices including lineage, metadata, and quality management.
- In-depth knowledge of data security, encryption, and compliance frameworks.
- Hands-on coding experience in languages commonly used in data engineering (e.g., Python, SQL, Scala).
Preferred Qualifications
- Experience building enterprise-wide data governance frameworks.
- Background working in large-scale distributed systems environments.
- Experience collaborating with cross-functional teams in complex enterprise environments.