Chapter Lead, Data Engineering

Cogeco•Quincy, MA

8d•Hybrid

About The Position

This leadership position combines deep technical expertise with people development. The Chapter Lead guides a team of Data Engineering Specialists, helps build their capabilities, and promotes high-quality, sustainable engineering solutions. The role also contributes hands-on to an agile squad for approximately 30% of the time and works with data partners and business stakeholders to deliver reliable data engineering solutions.

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; formal management experience is an asset.
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.
Proven experience building and optimizing ETL/ELT data pipelines.
Experience with or understanding of Agile methodologies.
People-first leadership approach focused on team well-being, continuous growth, and drawing on collective expertise with intellectual humility.
Results-oriented approach, with a bias for action, effective prioritization, and adaptability to new business domains.
Intellectual curiosity, ownership, and a rigorous standard for data quality and reliability.

Nice To Haves

Formal management experience.

Responsibilities

Manage a chapter of Data Engineering Specialists and support their professional growth through coaching, mentorship, and on-the-job development.
Define future data engineering skill needs, particularly those related to emerging AI technologies, and build the chapter’s capabilities accordingly.
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 that improve data quality, reliability, and accessibility.
Promote collaboration, knowledge sharing, continuous learning, and operational excellence within the chapter.
Work with Data Scientists, Analysts, and business partners to understand data needs and provide engineering solutions.
Conduct regular performance check-ins and annual performance reviews focused on growth and constructive feedback.
Assess chapter members’ capabilities to inform workforce planning, recruitment, and talent development.
Participate hands-on in an agile squad, contributing directly to its goals and deliverables for approximately 30% of the time.
Support implementation of Data Governance, security, and privacy policies, and provide feedback to improve those practices.