Manager - Data Engineering

We are seeking a Manager – Data Engineering with strong expertise in Python, Matillion, and Snowflake to lead the design, development, and delivery of scalable cloud-based data solutions. The ideal candidate will have a blend of technical expertise and leadership skills, with experience managing data engineering initiatives, mentoring team members, and collaborating with cross-functional stakeholders.

Key Responsibilities

- Lead the design, development, and implementation of enterprise-scale data engineering solutions using Python, Matillion, and Snowflake. - Manage end-to-end delivery of data integration, ETL/ELT, and data warehousing projects. - Architect scalable, high-performance data pipelines and optimize existing data platforms. - Mentor and guide data engineers through technical reviews, best practices, and career development. - Collaborate with business stakeholders, product owners, and solution architects to translate business requirements into technical solutions. - Drive data quality, governance, security, and operational excellence across data platforms. - Optimize Snowflake performance, including warehouse sizing, query tuning, and cost optimization. - Establish coding standards, CI/CD processes, and engineering best practices. - Manage project timelines, risks, resource planning, and stakeholder communication. - Support production deployments, issue resolution, and continuous platform improvements.

- 6+ years of experience in Data Engineering, with experience leading technical teams or projects. - Strong hands-on expertise in Python, Matillion, and Snowflake. - Advanced SQL and data modeling skills. - Experience building enterprise ETL/ELT pipelines and cloud data warehouse solutions. - Hands-on experience with cloud platforms such as AWS, Azure, or GCP. - Experience with Git, CI/CD, Agile/Scrum methodologies, and DevOps practices. - Strong leadership, stakeholder management, communication, and problem-solving skills.

- Experience with orchestration tools such as Airflow. - Exposure to DBT or similar data transformation frameworks. - Knowledge of data governance, security, and performance optimization. - Experience working with large-scale enterprise data platforms.