Data Architect

Description : Position overviewWe are looking for a seasoned Data Architect with deep expertise in cloud-native data platforms (AWS) along with Snowflake.The Data Architect will be responsible for designing and implementing enterprise-grade data platforms on AWS cloud using Snowflake, Python, PySpark and other cloud native tools and services. The role demands strong hands-on technical expertise in modern data engineering frameworks, data modeling, and architecture best practices, along with a solid understanding of data management, governance, and security principles.This role will collaborate with cross-functional teams to establish scalable, high-performing, and secure data ecosystems enabling advanced analytics, AI/ML, and BI use cases.Key Responsibilities : - Architect, Design and implement data Lakehouse, Data Warehouse solutions on AWS and Snowflake using Medallion Architecture (Bronze/Silver/Gold layers).- Define and implement end-to-end data pipelines and orchestration layer/ frameworks- Design for multi-structured data (structured, semi-structured, unstructured).- Define and develop architecture patterns for streaming, batch, and real-time data processing.- Integrate AWS data services (S3, Lake Formation, Kinesis, Lambda) with Snowflake into enterprise solutions.- Implement data quality, cataloging, lineage, and metadata management frameworks.- Partner with the data governance team to enforce standards for data ownership, stewardship, and lifecycle management.- Define policies for data security, masking, and access control aligned with organizational governance.- Drive adoption of best practices in DataOps, DevOps, and CI/CD for data engineering- Contribute to data strategy and roadmap creation aligned with enterprise objectives- Partner with business stakeholders (trading, risk, compliance) to translate requirements into technical architecture.- Provide technical leadership and guidance to engineering teams.Required Skills & Experience : - 15-18 years of experience in Data Engineering / Architecture, with at least 5 years in cloud-native data platforms (AWS) and Snowflake- Strong expertise in AWS and Snowflake services : S3, Glue, Lambda, Step Functions, IAM, CloudWatch, Snowpipe etc)- Expert-level proficiency in Snowflake schema design, performance tuning, ELT, security setup, and integration.- Strong programming skills in Python and PySpark for data transformation and automation.- Experience with ETL/ELT frameworks (Informatica, Matillion, DBT, Glue).- Good exposure and understanding of modeling, metadata management, data lineage, and master data concepts.- Good exposure of data governance frameworks (Collibra, Alation, or custom).- Exposure and experience to streaming technologies (Kafka, Kinesis) and API-based data integrations.- Strong understanding of security, compliance, and privacy frameworks (GDPR, HIPAA, etc.)- Strong problem-solving and analytical mindset.- Excellent communication and stakeholder management skills.- Ability to lead and mentor data engineering teams.- Self-driven, proactive, and capable of implementing technical initiatives end-to-end.Preferred Qualifications : - AWS Certified Data Analytics Specialty / AWS Solutions Architect certification.- SnowPro Core / SnowPro Advanced Architect Certification.- Experience working in multi-cloud or hybrid environments.- Exposure to Databricks or Azure Synapse considered a plus.Education : Bachelors or masters degree in computer science, Data Engineering, or related field. (ref:hirist.tech)