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Senior Data Engineer
Salesforce
Atlanta, USA
Full-time
Senior · 8+ years experience
Discovered 4 days ago
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- Partner closely with Product teams and business stakeholders to identify high-impact questions and translate business needs into scalable data models, metrics, analyses, and technical solutions
- Partner with business domain experts, Data Analytics, Data Science, and Engineering teams to build foundational datasets that are trusted, well understood, aligned with business strategy, and enable self-service analytics
- Design, build, and scale data models and pipelines that integrate and transform data from multiple sources into trusted, accessible datasets with measurable quality and predictable SLA performance
- Own the end-to-end lifecycle of metrics, analytical models, and data products, from initial exploration and prototyping through production, adoption, and ongoing maintenance
- Leverage AI-assisted development to accelerate engineering productivity while maintaining high standards for code, data quality, and maintainability, and build data foundations that enable automation and AI-native insights and decision-making
- Lead and influence the data strategy across multiple teams, domains, and use cases, driving alignment on scalable technical foundations and long-term investments
- Drive initiatives that expand access to trusted company metrics, enabling self-service analytics and faster, more consistent decision-making across Slack
- Establish, document, and promote data engineering best practices across Slack
- Mentor engineers and provide hands-on technical guidance, helping raise the technical bar across the organization
- You have 8+ years of overall software engineering or data engineering experience, including 5+ years of hands-on experience with data architecture, data modeling, data management, and metadata management
- You can independently structure and own ambiguous, high-impact problems from initial framing through technical strategy, execution, and measurable outcomes
- You bring strong autonomy, resourcefulness, and creativity when navigating complex technical, operational, and stakeholder constraints
- You have deep expertise in SQL and proven experience designing scalable data pipelines and data transformations that operate reliably across large and complex datasets
- You have a proven track record of architecting and optimizing data models, schemas, and processing workflows to improve performance, scalability, cost efficiency, and reliability in modern data warehouse environments
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