Data Engineer

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, Dev Ops, 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, Big Query, Redshift, Lake Formation, etc.).
Experience working in regulated domains (finance, healthcare, insurance) is desirable.