Senior Data Engineer ( Senior Consultant)

Key Responsibilities

• Develop, and maintain scalable ETL/ELT pipelines using dbt , Snowflake , and Airflow .
• Implement complex business transformation logic using SQL and Python .
• Design and optimize enterprise data models, data marts, and data warehouse solutions.
• Build, schedule, monitor, and troubleshoot workflows using Apache Airflow .
• Develop and automate deployment processes using GitLab CI/CD , including creation and management of jobs and runners .
• Ensure data quality, governance, observability, and performance optimization.
• Support AI/ML initiatives by building feature-ready datasets and scalable data pipelines.
• Collaborate with Data Scientists, Analysts, Architects, and business stakeholders to deliver data-driven solutions.
• Mentor team members and drive best practices in data engineering and software development.

Required Skills

• 13–14 years of experience in Data Engineering, ETL, Data Warehousing, or related domains.
• Strong hands-on experience with: dbt Snowflake Apache Airflow Python SQL
• dbt
• Snowflake
• Apache Airflow
• Python
• SQL
• Advanced SQL skills, including complex transformations, query optimization, and performance tuning.
• Strong Python programming experience for data processing, automation, and validation.
• Hands-on experience with GitLab , including: Source code management CI/CD pipeline creation GitLab Jobs GitLab Runners
• Source code management
• CI/CD pipeline creation
• GitLab Jobs
• GitLab Runners
• Strong understanding of Data Structures and Algorithms .
• Deep knowledge of ETL/ELT, Data Warehousing, Dimensional Modeling, and Data Governance.
• Experience working on AI/ML projects , including: Data preparation and feature engineering ML pipeline integration MLOps concepts Supporting model deployment and monitoring
• Data preparation and feature engineering
• ML pipeline integration
• MLOps concepts
• Supporting model deployment and monitoring

Preferred Skills

• Experience with AWS, Azure, or GCP.
• Exposure to Generative AI, RAG architectures, Vector Databases, or AI-powered analytics solutions.
• Experience leading technical teams and driving architecture decisions.

Education