Data Architect

Job Summary

We are looking for an experienced Data Architect to design and build scalable, secure, and high-performance data platforms. The ideal candidate should have a strong foundation in data engineering, data warehousing, and analytics, along with hands-on experience in cloud environments.

This role requires someone who understands end-to-end data workflows, from data ingestion to transformation and analytics, and can guide teams in building scalable, efficient, and reliable data solutions.

Key Responsibilities

• Design and implement scalable and reliable data architectures for enterprise data platforms.
• Build and optimize data pipelines, data models, and data warehouse solutions.
• Lead end-to-end data projects including requirement gathering, design, development, and deployment.
• Ensure data quality, consistency, and availability across systems.
• Improve performance, scalability, and cost-efficiency of data platforms.
• Work closely with business stakeholders to understand data requirements and translate them into technical solutions.
• Define and follow best practices for data engineering, data modeling, and data governance.
• Collaborate with cross-functional teams including data engineers, analysts, and business teams.
• Guide and mentor junior and mid-level data engineers.
• Support solution design and provide inputs during pre-sales or client discussions when required.

Required Skills & Experience

• 7+ years of experience in data engineering, data architecture, or related roles.
• Proven experience working as a Data Architect or in a similar capacity.
• Strong hands-on experience with SQL, data pipelines, and large-scale data processing.
• Good understanding of data modeling, ETL/ELT processes, and data warehousing concepts.
• Hands-on experience with at least one cloud platform (AWS / Azure / GCP).
• Experience designing and managing scalable data platforms and analytics systems.
• Strong problem-solving and analytical skills.
• Good communication skills and ability to work with stakeholders across teams.
• Experience leading teams or handling end-to-end project delivery is a plus.

Good to Have

• Experience with Snowflake and/or Databricks.
• Basic understanding of distributed data processing (e.g., Spark).
• Exposure to data governance concepts like data quality, lineage, and metadata management.
• Experience in multi-cloud environments.
• Familiarity with ML/AI data workflows (optional).