Job Title

Job Summary:Seeking an experienced Senior Data Engineer with over 9 years of industry experience to architect, build, and manage advanced data pipelines and platforms in a cloud environment. The ideal candidate will demonstrate hands-on expertise in ETL workflows, possess deep proficiency with Snowflake, and have a proven track record of implementing robust data governance and security practices.Key Responsibilities:- Architect, develop, and optimize scalable data pipelines for ingestion, processing, and storage of large data volumes from diverse sources. - Design, implement, and maintain end-to-end ELT/ETL workflows for seamless data integration using orchestration tools. - Manage data warehouse and data lake solutions, emphasizing Snowflake architecture, performance tuning, and cost optimization. - Implement, monitor, and enforce best practices for data governance, including data cataloguing, lineage, stewardship, access control, audit, and compliance. - Design and enforce rigorous data security policies and procedures for sensitive and regulated datasets, ensuring alignment with internal and external regulations. - Ensure high data quality, integrity, and reliability by deploying validation, monitoring, and alerting frameworks. - Collaborate with data science, analytics, DevOps, and business teams to fulfil analytics, BI, and operational data requirements. - Drive process automation, workflow optimization, and continuous process improvement in data engineering operations. - Mentor junior engineers, review code, and champion engineering excellence and compliance within the team. - Keep up to date on the latest trends in cloud data platforms, governance, and security; recommend and implement new technologies as appropriate.Required Skills & Qualifications:- Bachelor's or master's degree in computer science, Engineering, or related field. - 9+ years of full-lifecycle data engineering experience within enterprise environments. - Deep expertise in ETL pipeline development, orchestration (Airflow, Prefect, Dagster), and troubleshooting. - Advanced proficiency in Snowflake (data modelling, security, optimization, role-based access, etc.). - Strong foundation in data governance, cataloging, lineage, access management, and regulatory compliance best practices. - Demonstrated experience designing and implementing data security architectures (encryption, tokenization, masking, monitoring). - Proficiency with SQL and at least one programming language (Python preferred). - Exposure to distributed systems, cloud-native data platforms (AWS/GCP/Azure), and scalable storage technologies. - Excellent analytical, problem-solving, and stakeholder communication skills. - Experience mentoring or leading teams is an advantage.Preferred Qualifications:- Certifications in Snowflake, cloud platforms, or data security are a plus. - Familiarity with additional data warehouse/lake technologies (Databricks, BigQuery, Redshift, Lake Formation, etc.). - Experience working in regulated domains (finance, healthcare, insurance) is desirable.