Data Engineer at Sprout Social

, , Canada -

Full Time

Start Date

Immediate

Expiry Date

24 Dec, 25

Salary

165600.0

Posted On

25 Sep, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, ETL, ELT, SQL, Python, Data Modeling, Metadata Management, Data Infrastructure, Data Quality, Cloud Infrastructure, Data Products, Collaboration, Version Control, CI/CD, Testing, Observability

Industry

Software Development

Description

Sprout Social is looking for a Data Engineer to join our Data Foundations team. This team builds the internal data infrastructure, pipelines, and products that empower analytics, data science, and business stakeholders across Sprout. While our software engineers are focused on delivering customer-facing platform features, our data engineers specialize in ensuring data is reliable, well-modeled, and accessible to fuel smarter decisions and internal innovation. Why join Sprout Social’s Data Engineering team? Sprout Social empowers businesses worldwide to harness the immense potential of social media in today’s digital-first world. Processing over one billion social messages daily, our platform delivers insights and actionable intelligence to more than 30,000 brands. These insights guide strategic decisions, drive growth, and foster deeper connections with customers. Our Data Foundations team plays a critical role in this by enabling Sprout’s internal stakeholders—analytics, product, finance, sales, and beyond—to work with trustworthy, scalable, and reusable data. You’ll be helping build the pipelines, curated datasets, and data products that unlock value across the business and extend Sprout’s data-driven culture. What you’ll do 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. What you’ll bring 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. The minimum qualifications for this role include: 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. Preferred qualifications for this role include: 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). Experience implementing data quality frameworks, testing methodologies, and monitoring practices to ensure data integrity. Hands-on experience with event-driven or streaming frameworks (Kafka or NSQ, Kinesis, Pub/Sub). Proven ability to collaborate withcross-functional teams and effectively communicate complex technical concepts to non-technical stakeholders. Direct experience with cloud infrastructure (AWS, GCP, or Azure) and implementing cost optimization strategies for data platforms. How you’ll grow Within 1 month, you’ll plant your roots, including: Complete Sprout’s New Hire onboarding program and meet peers across Data Foundations, Data Science, Engineering. Learn the team’s existing data stack, pipelines, and modeling frameworks. Shadow teammates to understand how internal stakeholders use curated datasets today. Partner with your manager to scope your first pipeline or modeling task to own. Within 3 months, you’ll start hitting your stride by: Delivering your first production-ready pipeline, dataset, or internal data product. Collaborating with analysts and data scientists on requirements for reusable modeling layers. Gaining deeper familiarity with Sprout’s data warehouse(s) and orchestration environment—and starting to suggest improvements. Within 12 months, you’ll make this role your own by: Taking technical ownership of a set of pipelines or data products relied on by stakeholders across the business. Proposing and implementing improvements to our pipelines for scalability, reliability, or cost efficiency. Acting as a mentor to newer members of the Data Foundations team while continuing to grow your own expertise. Helping shape the team’s roadmap and long-term data foundations strategy. Of course what is outlined above is the ideal timeline, but things may shift based on business needs and other projects and tasks could be added at the discretion of your manager. Our Benefits Program We’re proud to regularly be recognized for our team, product and culture. Our benefits program includes: Insurance and benefit options that are built for both individuals and families Progressive policies to support work/life balance, like our flexible paid time off and parental leave program High-quality and well-maintained equipment—your computer will never prevent you from doing your best Wellness initiatives to ensure both health and mental well-being of our team Ongoing education and development opportunities via our Grow@Sprout program, employee-led diversity, equity and inclusion initiatives and mentorship programs for aspiring leaders Growing corporate social responsibility program that is driven by the involvement and passion of our team members The base pay range for this role is $110,400 (min), $138,000 (mid), $165,600 (max) CAD annually. Individual base pay is based on various factors, including work location, relevant experience and skills, the responsibility of the role, and job duties/requirements. The listed ranges represent the full earning potential in this position. Starting salaries for well-qualified new hires are typically around the midpoint of the range. These ranges were determined by a market-based compensation approach; we used data from trusted third-party compensation sources to set equitable, consistent, and competitive ranges. We also evaluate compensation bi-annually, identify any changes in the market and make adjustments to our ranges and existing employee compensation as needed. Base pay is only one element of an employee's total compensation at Sprout. Every Sprout team member has an opportunity to receive restricted stock units (RSUs) under Sprout’s equity plan. We have outlined the various components to an employee’s full compensation package here to help you to understand our total rewards package. Candidates for this remote work opportunity must be based in either British Columbia or Ontario. If you are based in another location within Canada, we aren’t able to hire in your location at this time; however, if you’d like to stay in touch with us in case that changes in the future, please apply and we’ll save your application for possible future consideration. #LI-REMOTE Sprout Social Inc. and its subsidiaries process personal data submitted through your application to assess your qualifications for employment and to inform our hiring decision and, where applicable, for required governmental reporting. For more information, please review Sprout's Global Applicant Privacy Notice.

Responsibilities

Design and maintain ETL/ELT pipelines and data workflows to ensure reliable and scalable data flows. Collaborate with various stakeholders to deliver curated datasets and internal data products.