About the Role :
We are seeking an experienced Data Architect to design and oversee the architecture of our enterprise data ecosystem. This role requires a deep understanding of data modeling, data integration, and cloud-based data solutions. You will collaborate with business and technology teams to create scalable, secure, and high-performing data platforms that enable analytics, reporting, and advanced insights.
Key Responsibilities :
- Design and implement enterprise-level data architecture strategies aligned with business needs.
- Define and maintain data models (conceptual, logical, and physical) for transactional, analytical, and big data systems.
- Lead the design of data pipelines, data lakes, and data warehouses ensuring scalability, performance, and cost optimization.
- Establish data governance, quality, and security standards across the organization.
- Collaborate with stakeholders to understand data requirements and translate them into architectural blueprints.
- Evaluate and recommend tools, technologies, and cloud platforms (AWS, Azure, GCP, Snowflake, etc.) to optimize data solutions.
- Guide ETL / ELT developers, data engineers, and BI teams in implementing best practices.
- Monitor, troubleshoot, and optimize data systems for performance and reliability.
- Act as a thought leader, mentoring team members and contributing to the companys overall data strategy.
Key Requirements :
Bachelors or Masters degree in Computer Science, Information Systems, or a related field.8+ years of experience in data engineering, data warehousing, or database development.Proven experience in designing and implementing data architectures at scale.Strong expertise in SQL, relational databases, and data modeling techniques (OLTP, OLAP, dimensional modeling).Hands-on experience with ETL / ELT tools (Informatica, Talend, DataStage, SSIS, etc.).Proficiency in cloud platforms (AWS Redshift, Azure Synapse, GCP BigQuery, Snowflake).Solid understanding of data governance, MDM, metadata management, and security frameworks.Strong analytical, problem-solving, and communication skills.Good to Have :
Familiarity with big data technologies (Hadoop, Spark, Kafka).Experience in NoSQL databases (MongoDB, Cassandra, etc.).Exposure to machine learning data pipelines and real-time analytics.Knowledge of DevOps, CI / CD, and infrastructure-as-code for data solutions.(ref : hirist.tech)