Manager, Data Engineering at Sprout Social

, , Canada -

Full Time

Start Date

Immediate

Expiry Date

30 Jan, 26

Salary

250700.0

Posted On

01 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, DataOps, Cloud Data Warehouses, Dimensional Modeling, Data Vault Principles, Automated Testing, Monitoring, Data Governance, API Integration, Change Data Capture, Incremental Load Patterns, Cross-Functional Collaboration, Performance Management, Career Development, Incident Response, Technical Strategy

Industry

Software Development

Description

Description Sprout Social is looking to hire an Engineering Manager for the Data team to lead the technical strategy and execution of our data platform. You'll define the architecture roadmap, establish DataOps practices, build the team's capability to deliver iteratively, and create the conditions for broader data ownership across the organization. This is a hands-on leadership role for someone who can balance foundations with forward momentum. Why join Sprout’s Data team? At Sprout, we've only scratched the surface of what's possible with our data. This is a unique opportunity to shape a data function at an inflection point. You'll join a growing team that's been building governance foundations to power AI capabilities, now ready to scale both in size and technical sophistication. You'll have meaningful influence on technical direction and how data serves the business. We value pragmatism over perfection, iterative progress over grand transformations, and collaboration over hierarchy. If you want autonomy to build something that matters, the space to experiment and innovate, and the chance to grow engineers while growing yourself—this is the role. What you’ll do Lead iterative delivery of data products using vertical thin-slicing—shipping usable improvements in weeks, not quarters Build pipelines and models using dimensional or Data Vault methodologies to make data more trusted and consumable Build automated data certification workflows that flow into our catalog, enabling self-service discovery Partner with Product, Finance, Operations, and Sales to translate business questions into scalable technical solutions Grow and mentor a team of data and analytics engineers focused on execution and impact Implement DataOps practices—CI/CD, automated testing, monitoring—that make data reliable by default Present progress and technical decisions to leadership in terms of business outcomes, not just infrastructure What you’ll bring You're a builder and executor who's worked in SaaS or B2B environments where strong foundations and standards are critical to data adoption. You've moved data from API sources into warehouses, applied formal modeling principles, and made those models discoverable and actionable. You think in products, not just pipelines. You lead with context, empower your team with clarity, and deliver results that move the business forward. The minimum qualifications for this role include: 10+ years of professional experience in data engineering 4+ years of experience formally managing engineering teams, including direct responsibility for hiring, performance management, and career development cycles Led the planning and execution of a major data architecture refactoring or modernization project within an existing production environment. Built production pipelines using cloud data warehouses (Snowflake, BigQuery, Redshift), dbt, and orchestration tools (Airflow) Applied dimensional modeling or Data Vault principles to design subject areas consumed by BI and AI tools Implemented data governance tooling including cataloging, lineage tracking, and automated quality checks Preferred qualifications for this role include: Built data models supporting SaaS metrics: ARR, retention cohorts, product adoption funnels, customer health scores, sales pipeline Experience integrating API-based sources (REST, GraphQL) with change data capture and incremental load patterns Deployed automated data certification workflows that validate models before publishing to catalogs (DataHub, Secoda, Select Star) Led cross-functional initiatives involving Product, Finance, and Go-to-Market teams with documented stakeholder impact Contributed to or led incident response for data pipeline failures affecting business-critical reporting How you’ll grow Within 1 month, you’ll plant your roots, including: Familiarizing yourself with team structure, roles, and roadmap Meeting stakeholders across Product, Finance, Operations, and Sales to understand pain points and priorities Auditing existing pipelines, models, and tooling to identify quick wins and longer-term opportunities Establishing weekly rituals for team sync, stakeholder updates, and iterative delivery cadence Within 3 months, you’ll start hitting your stride by: Shipping your first data models with measurable improvements in adoption or trust Implementing automated quality checks and lineage tracking for high-priority datasets Growing your existing team and fostering inclusive collaboration with analysts and data scientists to enable domain ownership Presenting your first progress update to leadership showing delivered value, not just activity Within 6 months, you’ll be making a clear impact through: Delivering a certified, cataloged dataset used by multiple teams for critical reporting or analysis Establishing DataOps practices that reduce pipeline failures and speed up delivery cycles Creating pathways for technically capable contributors outside your team to build and certify data products within governance guardrails Leading at least one cross-functional project that drives measurable business outcomes (e.g., faster financial close, improved sales forecasting) Creating visibility into team performance through metrics that matter to stakeholders Within 12 months, you’ll make this role your own by: Owning the technical vision for Internal Data Products with a roadmap others rally behind Delivering a portfolio of trusted data products that power OKR metrics and operational decisions Building a high-performing team known for execution, collaboration, and raising the bar Establishing your team as the go-to partner for turning business questions into data solutions Shaping how the company thinks about data governance, quality, and self-service analytics 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 $167,100 (min), $208,900 (mid), $250,700 (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. 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

Lead the technical strategy and execution of the data platform, defining the architecture roadmap and establishing DataOps practices. Grow and mentor a team of data and analytics engineers while delivering data products iteratively.