Senior Data Engineer

We are seeking an experienced Senior Data Engineer / Lead Data Engineer with strong expertise in Data Vault 2.0, DBT/Coalesce, Snowflake, PySpark, AWS, and Airflow. The ideal candidate will lead data architecture and engineering initiatives, establish data modeling standards, drive technical decision-making, and mentor engineering teams while delivering scalable and high-performance data platform solutions.

Key Responsibilities

• Design, develop, and implement enterprise-scale data platforms using Data Vault 2.0 methodology.
• Lead end-to-end implementation of DBT and/or Coalesce-based data transformation frameworks.
• Architect and build scalable data solutions on Snowflake and cloud-native platforms.
• Develop and optimize complex SQL queries, ETL/ELT pipelines, and data integration processes.
• Build and maintain data pipelines using PySpark, AWS services, and Apache Airflow.
• Lead solution design sessions, architecture reviews, and technical discussions with stakeholders.
• Define and enforce Data Vault standards, governance policies, naming conventions, and best practices.
• Conduct code reviews and ensure adherence to engineering standards and data quality requirements.
• Collaborate with business stakeholders, architects, product owners, and delivery teams to translate requirements into scalable solutions.
• Drive technical decision-making, estimation, sprint planning, and delivery execution.
• Troubleshoot performance bottlenecks and implement optimization strategies across data platforms.
• Mentor and guide junior and mid-level engineers through technical leadership and knowledge sharing.

Required Skills & Experience

• 8+ years of experience in Data Engineering and Data Warehousing.
• Strong hands-on experience with Data Vault 2.0 architecture and implementation.
• Extensive experience with DBT and/or Coalesce.
• Strong expertise in Snowflake Data Cloud.
• Advanced SQL development and performance tuning skills.
• Hands-on experience with PySpark and distributed data processing.
• Experience with AWS services (S3, Glue, Lambda, EMR, IAM, Redshift, etc.).
• Strong experience in workflow orchestration using Apache Airflow.
• Expertise in ETL/ELT design, data modeling, and data integration patterns.
• Experience leading architecture discussions, technical reviews, and large-scale data transformation programs.
• Strong communication and stakeholder management skills.

Preferred

• Data Vault 2.0 certification or relevant data architecture certifications.
• Experience with Agile/Scrum delivery methodologies.
• Knowledge of CI/CD, DevOps, and Infrastructure as Code practices.
• Experience with data governance, metadata management, and data quality frameworks.
• Exposure to modern analytics and reporting ecosystems.