Sprout Social is looking for a Data Engineer to join their Data Foundations team to build and maintain the internal data infrastructure, pipelines, and products that empower analytics, data science, and business stakeholders across the company, ensuring data is reliable, well-modeled, and accessible to fuel smarter decisions and internal innovation.
Requirements
- 2+ years of professional experience in data engineering or at least 2 years of hands on experience building, deploying and maintaining production-grade data infrastructure and pipelines
- Demonstrated proficiency in SQL (e.g. MySQL, PostgreSQL) and data modeling; with experience in a variety of business domains. Proficiency in Python.
- Experience working in relational and non-relational databases
- Hands on experience with ELT + transformation frameworks (e.g., dbt) and with orchestrators (e.g., Airflow, dbt. dagster).
- Experience building internal data products (curated datasets, semantic layers, or reusable modeling frameworks).
- Proven experience applying standard software development practice to data engineering, including testing, version control, code reviews, incident management, incident CI/CD, documentation, and observability for data.
- Experience building and maintaining data infrastructure using transformations with dbt or similar tools(and managing semantic layers for Business intelligence (BI) dashboards (e.g. Tableau, Hex, Looker).
- Hands-on experience with event-driven or streaming frameworks (Kafka or NSQ, Kinesis, Pub/Sub).
- Direct experience with cloud infrastructure (AWS, GCP, or Azure) and implementing cost optimization strategies for data platforms.
Responsibilities
- Design and maintain ETL/ELT pipelines and data workflows that enable reliable, timely, and scalable data flows.
- Collaborate with analysts, scientists, and business stakeholders to deliver curated datasets and internal data products.
- Implement best practices in schema design, data modeling, and metadata management.
- Own and evolve internal data infrastructure for quality, monitoring, and discoverability.
- Partner with software engineering teams where application data intersects with internal pipelines—ensuring business-critical data is clean, structured, and usable.
- Experience building internal data products (curated datasets, semantic layers, or reusable modeling frameworks).
- Proven experience applying standard software development practice to data engineering, including testing, version control, code reviews, incident management, incident CI/CD, documentation, and observability for data.
Other
- We’re looking for a data engineer with a strong foundation in data infrastructure and a passion for enabling others to succeed through high-quality data.
- Proven ability to collaborate with cross-functional teams and effectively communicate complex technical concepts to non-technical stakeholders.
- Individual base pay is based on various factors, including work location, relevant experience and skills, the responsibility of the role, and job duties/requirements.
- Sprout Social is proud to be an Equal Opportunity Employer and an Affirmative Action Employer.
- If you require a reasonable accommodation for any part of the interview process or to submit your application, please email us at accommodations@sproutsocial.com.
