Data Engineering Manager - $230k to $280k + Benefits - Hybrid (Austin TX) - Consultancy

About the Role:

We are seeking a highly skilled and motivated Data Engineering Manager to lead our clients data engineering team. In this role, you will be responsible for architecting and building scalable data infrastructure, managing a team of data engineers, and ensuring the delivery of high-quality data solutions that support data-driven decision-making across the organization.

Key Responsibilities:

• Team Leadership & Management:
• Hire, mentor, and lead a team of data engineers.
• Foster a collaborative, high-performance team culture.
• Conduct regular 1:1s, performance reviews, and career development sessions.
• Technical Leadership:
• Design, develop, and maintain robust and scalable data pipelines and ETL processes.
• Oversee data architecture decisions, ensuring scalability, reliability, and performance.
• Implement best practices for data modelling, data quality, and metadata management.
• Collaboration & Strategy:
• Work cross-functionally with data scientists, analysts, product managers, and other engineering teams.
• Align data engineering efforts with broader business goals and data strategy.
• Prioritize projects and allocate resources effectively.
• Operations & Governance:
• Ensure data security, privacy, and compliance with relevant regulations (e.g., GDPR, HIPAA).
• Monitor and optimize data infrastructure performance and costs.
• Establish and enforce data engineering standards and documentation practices.

Required Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 6+ years of experience in data engineering or software engineering roles.
• 2+ years in a technical leadership or management position.
• Strong experience with cloud data platforms (e.g., AWS, GCP, Azure).
• Proficiency in SQL, Python, and data pipeline tools (e.g., Apache Airflow, dbt, Spark).
• Familiarity with data warehousing solutions (e.g., Snowflake, BigQuery, Redshift).

Preferred Qualifications:

• Experience managing remote or distributed teams.
• Knowledge of modern data stack tools and concepts.
• Background in agile development and CI/CD for data workflows.
• Understanding of ML pipelines and data science workflows is a plus.