About the position
As a Senior Data Engineer, you will be responsible for championing the trust and quality of our data. Our mission is to develop and maintain dependable, trusted, and well-governed data models and metrics that ensure consistency, accuracy, and timely access to insights. In this role, you will work cross-functionally with business domain experts, analytics, and engineering teams to design and implement our data warehouse model. You will design, build, and scale data pipelines that transform billions of records into actionable data models—enabling impactful insights. You will lead initiatives to formalize data governance and management practices, streamline our information lifecycle, and define key company metrics. You will also provide mentorship and hands-on technical support to help build trusted and reliable data products. You have deep technical expertise, thrive in a developing data ecosystem, and can help establish a strong data foundation for the company. You’re a self-starter—detail-oriented, quality-driven, and passionate about making a significant impact at Slack.
Responsibilities
- Translate business requirements into data models that are easy to understand and used by different disciplines across the company.
- Design, implement and build pipelines that deliver data with measurable quality under the SLA.
- Partner with business domain experts, data analysts, data science and engineering teams to build foundational data sets that are trusted, well understood, aligned with business strategy and enable self-service.
- Champion the overall strategy for data across multiple teams and different use cases.
- Increase access to foundational company metrics through process and technical foundations.
- Identify, document and promote data engineering best practices throughout Slack.
- Build systems that enable automation and AI-native insights generation and decision-making.
Requirements
- Over 5 years of hands-on experience in data architecture, data modeling, master data management, and metadata management.
- A total of 8+ years of overall experience in software engineering.
- Proven track record of scaling and optimizing schemas, and performance tuning SQL and ETL pipelines in OLAP and data warehouse environments.
- Proficiency in at least one programming language commonly used within Data Engineering, such as Python or Java.
- Hands-on experience with Big Data technologies such as Snowflake, Spark, Airflow, and Hive.
- Recent accomplishments working with both relational and NoSQL data stores, as well as various data modeling approaches.
- Familiarity with data governance frameworks, the software development life cycle (SDLC), and Agile methodologies.
- Excellent written and verbal communication skills, along with strong interpersonal abilities to collaborate effectively with both technical and business stakeholders.
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent training, fellowship experience, or relevant work experience.
Benefits
- Time off programs
- Medical, dental, vision
- Mental health support
- Paid parental leave
- Life and disability insurance
- 401(k)
- Employee stock purchasing program
