Chapter Lead, Data Engineering

Cogeco•Quincy, MA

5d•Hybrid

About The Position

This leadership position combines deep technical expertise with a commitment to people development. The Chapter Lead guides Data Engineering Specialists, builds the team’s capabilities for evolving domain needs—particularly emerging AI technologies—and helps deliver high-quality, sustainable engineering solutions. The role includes hands-on work as an active member of an agile squad for approximately 30% of the time. The position is located in Quincy, Massachusetts, and is listed as hybrid.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related technical discipline.
At least 7 years of experience in data engineering or software engineering with a data focus.
At least 3 years of experience in leadership, mentorship, or coaching.
Proficiency in writing complex, optimized SQL queries.
Understanding of data formats and their applications, including SQL, Filestore, Objectstore, and NoSQL.
Advanced Python programming skills for data engineering, including tools such as Pandas, PySpark, and pipeline frameworks such as Airflow or Dagster.
Deep experience with cloud data platforms such as GCP, AWS, or Azure, including data warehousing platforms such as BigQuery, Snowflake, or Redshift, and data processing services.
Experience building and optimizing ETL/ELT data pipelines.
Experience with or understanding of Agile methodologies.
People-first leadership focused on team well-being, continuous growth, and using collective expertise with intellectual humility.
Results-oriented approach, bias for action, effective prioritization, and adaptability to new business domains.
Intellectual curiosity, ownership, and high standards for data quality and reliability.

Nice To Haves

Formal management experience is a strong asset.

Responsibilities

Manage a chapter of Data Engineering Specialists, supporting their professional growth through coaching, mentorship, and on-the-job development.
Define future data engineering skills, particularly those related to emerging AI technologies, and build the chapter’s capabilities to meet changing domain demands.
Lead the design, development, and maintenance of robust, scalable, and reliable data pipelines and infrastructure.
Establish best practices for coding standards, CI/CD, testing, and infrastructure management.
Collaborate with the Data Architecture team to propose and implement architectural solutions and strategies that improve data quality, reliability, and accessibility.
Promote a collaborative chapter environment through knowledge sharing, continuous learning, and operational excellence.
Work with Data Scientists, Analysts, and business partners to understand data needs and provide engineering solutions.
Conduct performance check-ins and annual reviews focused on growth and constructive feedback.
Assess chapter members’ capabilities to inform workforce planning, recruitment, and talent development.
Spend approximately 30% of the time as an active, hands-on member of an agile squad, contributing to its goals and deliverables.
Support implementation of Data Governance, security, and privacy policies, and provide feedback to improve those practices.