Safelite is looking to modernize key legacy data pipelines, focusing on data ingestion, replication, and continuous integration. The goal is to create a streamlined and efficient data environment that supports data availability for key technical consumers, ultimately leading to the decommissioning of legacy tools.
Requirements
- Extensive experience with ETL/ELT jobs and data pipelines using tools such as Airflow, Fivetran, Airbyte, etc. (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)
- Proficiency in Python or similar programming languages. (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 Fivetran, Snowflake, DBT, Airflow, and Tableau.
- Work to rebuild functionality and reporting present in our legacy reporting tools (IBM Datastage/IBM Cognos) with new functionality in our modern data stack, ultimately resulting in our ability to decommission legacy tools.
- Own change management for the data engineering team. Review and approve PRs, change requests, and collaborate with other engineering teams on deployment schedules and impact assessments.
- Review and own security posture of the data engineering team to ensure company data is adequately accessible to those who need it, but inaccessible to those who don't. Ensure logging is sufficient to monitor and alert on data access attempts.
- Own the on-call rotation schedule, playbooks, and alerting functions for the data engineering team.
- Analyze and deconstruct complex operational and financial reporting workflows from legacy systems. Collaborate with stakeholders to refine the data team's understanding and documentation of source system processes, ultimately resulting in user stories that allow fact/dimensional star schema modeling that addresses stakeholder business requirements.
- 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.
Other
- Partner with other data leaders and product management function to build project timelines and keep initiatives on track.
- Foster a culture of ownership where data engineers are empowered to become experts in their assigned business domain verticals.
- 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.
