Job description
Data Engineer
Why work at SMG?
SMG is a leading experience management (XM) provider, serving restaurants, retailers, and other multi-location consumer businesses by changing how brands act on customer + employee insights. With a rich 30-year history, SMG is uniquely pairing an enterprise software platform with professional services to help brands generate new revenue, grow existing revenue, reduce detractors, and drive operational efficiencies. And with our 2024 acquisition of Bulbshare, we also help the world’s leading organizations grow through real-time customer collaboration by building mobile-first customer communities in over 30 markets worldwide, enabling clients to collaborate with consumers quickly and effectively for insights, ideation, and advocacy.
We offer our talent -
- Work hard, have fun environment - We work hard to deliver a fulfilling, exciting workplace environment for each SMG employee. Our teams are composed of smart, talented, curious people who love a good challenge.
- Values driven culture where we connect, collaborate & co-create.
- Remote first company (fully remote)
- Unlimited PTO
- Tech provided
- Company sick pay
Diverse, experienced, friendly team which will welcome you, support you and challenge you. We are proud to be an equal opportunity employer. We celebrate diversity and create an inclusive work environment in which all our colleagues experience belonging, have their unique needs respected and met, have equal access to opportunities and resources, and feel fully engaged to contribute to the company’s success.
As a Senior Data Engineer at SMG, this is what you will do:
- Lead by example in data engineering practices, demonstrating expertise in a variety of technologies, including but not limited to Python, SQL, dbt, Snowflake, Airflow, Kafka, and other relevant technologies in the data engineering domain. Experience with scaling to high volumes is highly desirable.
- Inspire and mentor data engineering teams, fostering a growth mindset and a collaborative environment. Lead initiatives to rebuild the team and instill a culture of continuous learning and improvement.
- Expertise in building deployment pipelines for data related workflows (e.g. Github Actions/Azure DevOps pipelines).
- Collaborate with leadership to shape the company’s vision for data engineering, providing valuable insights and guidance on technological strategies and opportunities.
- Drive efforts to refactor and rebuild our aging data infrastructure, prioritizing scalability, reliability, and maintainability.
- Identify and address areas of technical constraints in data engineering, implementing strategies to gradually reduce their impact on delivering value.
- Champion modern data engineering practices, including data modeling, ETL processes, data quality assurance, and data pipeline orchestration.
- Advocate for tidy code practices in data engineering, shepherd code review processes, and utilize modern code tooling to ensure high-quality software delivery.
- Collaborate cross-functionally with other teams to solve complex technical challenges in data engineering and drive innovation across the organization.
- Lead data engineering teams to deliver significant initiatives successfully, managing timelines, resources, and risks effectively.
You are a perfect match for the role if you have:
- Bachelor’s degree in computer science, engineering, or related field or equivalent experience.
- Extensive experience (4+ years) in data engineering, focusing on leading teams and initiatives to deliver value.
- Proven expertise in various data engineering technologies, including but not limited to SQL, Python, dbt, Snowflake, Apache Spark, Kafka, Airflow, and other relevant technologies in the data engineering domain.
- Strong understanding of modern data engineering practices, including data modeling, ETL processes, data quality assurance, and data pipeline orchestration.
- Experience with data engineering tooling and platforms such as Databricks and Snowflake is highly desirable.
- Excellent leadership and communication skills, with a record of leading efforts on collaborative and high-performing data engineering teams.
- Ability to quickly learn and adapt to innovative data technologies as needed.
- Ability to thrive in a dynamic, fast-paced environment with a growth mindset and a commitment to continuous learning.
- Demonstrated ability to drive change and influence stakeholders at all levels of the organization.
About SMG:
To learn more about our customer, employee, and brand experience management (XM) solutions, visit www.smg.com.
