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.