Manager of Data Engineering

About the Role

Key Responsibilities

• Leadership, Mentorship and Day to Day Management of Data Engineering Pods and Resources
• Development of DBT Pipelines for data transformation, including cataloging, lineage, freshness, and data quality checks. Implement best practices to optimize data transformation processes.
• Conduct thorough code reviews to ensure the quality, efficiency, and maintainability of data engineering code. Provide constructive feedback and mentor team members to improve their skills.
• Hold the data engineering team accountable for adhering to code quality, dbt best practices, and data governance standards. Establish and enforce coding standards and guidelines.
• Collaborate with the Data Platform Team to define and maintain the infrastructure for data engineering code. Ensure scalability, reliability, and performance of data pipelines.
• Implement and maintain Airflow workflows and DAGs to orchestrate data pipelines effectively. Ensure the quality and reliability of workflow scheduling and execution.
• Leverage Google Cloud Platform (GCP) technologies such as Pub/Sub, DataFlow, Cloud Functions, BigQuery, and Cloud Storage to design and optimize data solutions.
• Lead and mentor a team of data engineers, fostering a culture of collaboration, continuous learning, and innovation. Provide guidance on technical and career development.
• Collaborate closely with data scientists, analysts, and other stakeholders to understand their data requirements and provide data engineering support.
• Stay updated with the latest advancements in Agentic AI and RAG Technologies. Evaluate and integrate as appropriate into data engineering processes to enhance data retrieval, generation, and overall efficiency.
• Lead the integration of Vibe coding practices into data engineering processes. Define and enforce guardrails to ensure ethical and responsible usage of Vibe Coding, collaborate with cross-functional teams to establish best practices, and mentor the team on better prompting, style guides, and tooling choices to improve accuracy and results.

Requirements

• Bachelor's degree in a relevant field (e.g., Data Science, Computer Science, Business Analytics); master's degree preferred.
• Proven experience in data engineering, with at least 2 years in a leadership or managerial role.
• Expertise in DBT for data transformation, including cataloging, lineage, freshness, and data quality checks.
• Strong understanding of data governance principles and best practices.
• Proficiency in Airflow and DAG development.
• Experience working with Google Cloud Platform (GCP) technologies.
• Excellent coding skills in languages such as Python and SQL.
• Strong leadership, communication, and problem-solving skills.
• Knowledge of Agentic AI, RAG, and Vibe Coding Technologies and their implementation into data practices.
• This role requires onsite presence 4 days/week in the Chicago office (Fulton Market District).

Nice to Have

• Experience with implementing and managing data pipelines in cloud environments.
• Familiarity with data orchestration and workflow automation tools.
• Experience with ethical AI practices and responsible data management.

Qualifications

• Bachelor's degree in a relevant field (e.g., Data Science, Computer Science, Business Analytics); master's degree preferred.
• Proven experience in data engineering, with at least 2 years in a leadership or managerial role.

Benefits & Perks

• A generous benefits package that includes paid time off, health, dental, and vision insurance.
• 401(k) savings plan with company match.
• Salary range: $145,000-186,000/year plus performance bonus.