G2 - Data Platform, Manager

Unknown1w ago

Requirements

• We realize applying for jobs can feel daunting at times. Even if you don’t check all the boxes in the job description, we encourage you to apply anyway. • 8+ years of experience in data engineering, data platforms, or cloud data architecture, with 3+ years in engineering leadership roles. • Strong expertise in SQL, Python, data modeling, ELT/ETL development, and modern data architecture patterns. • Hands-on experience with Snowflake and AWS data services (EKS, S3, Lambda, Glue, Redshift). • Experience with orchestration and transformation tools such as Airflow, dbt, or similar technologies. • Deep understanding of data warehouse, lakehouse, and enterprise data platform architectures. • Experience implementing data quality, lineage, metadata management, and observability solutions. • Proven ability to lead, mentor, and develop high-performing engineering teams. • Strong stakeholder management, communication, and execution skills. • Ability to balance platform reliability, governance, delivery, and long-term technical vision. • What Can Help Your Application Stand Out: • Proficiency in data modeling, schema design, and optimizing data structures for performance in Snowflake. • Working experience in startup environments. • Experience with Agile process methodology, CI/CD automation, Test Driven Development. • Knowledge of data governance, security, and compliance standards within cloud-based data solutions. • Understanding of any reporting tools such as Tableau, Qlikview ,Looker or PowerBI. • Database administration background. • Our Commitment to Inclusivity and Diversity • At G2, we are committed to creating an inclusive and diverse environment where people of every background can thrive and feel welcome. We consider applicants without regard to race, color, creed, religion, national origin, genetic information, gender identity or expression, sexual orientation, pregnancy, age, or marital, veteran, or physical or mental disability status. Learn more about our commitments here. • For job applicants in California, the United Kingdom, and the European Union, please review this applicant privacy notice before applying to this job. • How We Use AI Technology in Our Hiring ProcessG2 incorporates AI-powered technology to enhance our candidate evaluation process. These tools may assist with initial application screening, skills assessment analysis, and identifying candidates whose qualifications align with specific role requirements. While AI technology supports our recruitment workflow, all final hiring decisions remain under human oversight and judgment. • How We Use AI Technology in Our Hiring Process • Your Choice Matters: If you would prefer that your application be reviewed without AI assistance, you can opt out by entering your email address in the email entry field at the bottom of the Automated Processing Legal Notice. Choosing to opt out will not disadvantage your application in any way—we will ensure your materials receive a thorough manual review by our hiring team.For additional details about how we handle your information throughout the application process, please review G2's Applicant Privacy Notice. • Your Choice Matters:

Responsibilities

• Data Platform & Pipeline Strategy and Delivery (40%): • Own the roadmap and delivery of scalable data platform capabilities across ingestion, transformation, storage, serving, and access layers. • Guide teams in designing robust, reusable, and secure platform solutions for analytics, ML, AI, and product use cases. • Define and enforce platform architecture standards, engineering best practices, and development patterns. • Partner with engineering, analytics, and product teams to ensure data is reliable, discoverable, and accessible. • Drive adoption of modern data architecture practices, including data products, self-service analytics, metadata management, and automation. • Evaluate and influence technology choices to improve scalability, reliability, developer productivity, and cost efficiency. • Platform Reliability, Governance and Operations (35%) • Establish accountability for platform reliability, availability, performance, and operational excellence. • Define and manage platform SLAs/SLOs for critical data services and capabilities. • Drive implementation of data quality, observability, lineage, monitoring, and alerting frameworks. • Partner with security and governance teams to implement scalable access controls, compliance standards, and data protection practices. • Lead incident management, root cause analysis, and continuous improvement of platform operations. • Optimize cloud and platform costs through performance tuning, workload management, and resource governance. • Leadership and Mentoring (40%): • Lead and develop high-performing data platform engineering teams, including engineers and technical leads. • Set clear goals, priorities, and expectations while supporting career growth and technical development. • Build a culture of ownership, collaboration, engineering excellence, and operational discipline. • Plan team capacity, hiring, onboarding, and succession to support current and future platform needs. • Translate business priorities into executable technical roadmaps. • Communicate platform progress, risks, trade-offs, and decisions effectively with senior stakeholders.