Manager of Data Engineering

Safelite•Columbus, OH

7d•Onsite

About The Position

The Manager of Data Engineering at Safelite is responsible for modernizing key legacy data pipelines, focusing on data ingestion, replication, and continuous integration. This role will oversee the development, maintenance, and enhancement of key data infrastructure, ensuring data quality and reliability. Additionally, the Manager will serve as a player-coach to a team of data engineers. The expected outcome is a streamlined and efficient data environment that supports data availability for key technical consumers ranging from analytics engineers to embedded analysts.

Requirements

Bachelor's Degree in computer science, engineering, analytics, or related field
4-6 years hands on experience in a data engineering or analytics related role
1-3 years managing a technical team
Extensive experience with ETL/ELT jobs and data pipelines using tools such as Buildkite, AWS Glue, and Informatica. (High proficiency)
Proficiency in cloud data warehouses (e.g., Snowflake, BigQuery) and relational databases. (High proficiency)
Advanced SQL skills, including window functions, CTEs, and nested queries. (High proficiency)
Experience with script-based data transformation tools (e.g., dbt, Talend). (High proficiency)
Ability to train and guide developers in using version control tools like GitHub. (High proficiency)
Deep understanding of data architecture principles. (High proficiency)
Ability to collaborate with cross-functional teams. (High proficiency)
Experience managing and mentoring data teams. (Medium proficiency)
Experience with legacy data tools, such as mainframe systems, Oracle, and Informatica. (Medium proficiency)
Ability to orchestrate complex workflows using tools like Apache Airflow or Dagster. (Medium proficiency)
Strong understanding of data governance and security practices. (Medium proficiency)
Proficiency in Python or similar programming languages. (Medium proficiency)
Leadership skills with experience in project management. (Medium proficiency)

Responsibilities

Lead the effort to modernize and enhance legacy data ingestion processes, ensuring they are efficient, scalable, and maintainable using tools such as AWS Glue or Apache Kafka
Design and build scalable ETL pipelines to automate data ingestion from various sources into a centralized data lake and enable a proactive posture toward consuming source system updates and changes.
Develop and deploy continuous integration and continuous deployment (CI/CD) pipelines to automate and streamline data engineering workflows.
Enhance monitoring and alerting systems to proactively identify and resolve issues, minimizing downtime and ensuring data quality.
Analyze and deconstruct complex operational and financial reporting workflows from legacy systems. Rebuild these workflows using modern cloud-based tools, ensuring they are optimized for performance and scalability.
Collaborate with stakeholders to ensure the new workflows meet business requirements and improve reporting accuracy and efficiency.
Serve as a player-coach, providing technical guidance and mentorship to a team of skilled data engineers.
Develop training programs and resources to enhance the team's technical capabilities and ensure successful maintenance and scaling of new tools and processes.
Work closely with peers and leaders across the engineering and business organizations to align data engineering efforts with overall company goals.
Participate in cross-functional projects to integrate source system changes into downstream data pipelines and reporting assets.
Ensure data engineering solutions are aligned with business needs and support data-driven decision-making.
Manage costs associated with running Data infrastructure and operations.
Performs other duties as assigned
Complies with all policies and standards