Senior Data Engineer

Supplier.io

11h

About The Position

Supplier.io is expanding our data engineering team and is seeking a Senior data Engineer to play a critical role in scaling and modernizing our data platform. This role is ideal for a highly experiences, hands-on engineer who thrives in complex environments, brings strong architectural thinking, and enjoys mentoring others while collaborating across teams, geographies, and disciplines. As a Senior Data Engineer, you will drive, shape and execute our long-term data strategy, design resilient and scalable data architectures, and technical excellence across our data ecosystem. You will work closely with product, Analytics, Infrastructure and Engineer teams to ensure our data systems support business growth, advance analytics and data-driven decision making. To support Supplier.io growth, we are investing heavily in cloud-native, data-driven technologies. This role will be instrumental in leveraging modern data services, optimizing cost, and ensuring our data platform is secure, reliable, and scalable.

Requirements

Bachelor of Computer Science, Management Information System, Engineering, Data Science, or related field.
7+ years of progressive experience in data engineering with demonstrated ownership of complex data systems in production environments. At least 2 years in a senior or lead capacity preferred.
Advanced experience designing, building, and supporting Snowflake based solutions at scale.
Proven experience architecting and implementing large-scale data solutions (i.e. Azure, AWS, GCP, or multi-cloud environments).
Strong expertise in data modeling, ETL/ELT processes, and modern data warehousing principles.
Advanced proficiency with Snowflake, Python and SQL, building reliable, testable data pipelines.
Strong experience with big data technologies, orchestration frameworks, and data pipeline tools. (i.e. Airflow, dbt, Spark, or similar)
Experience working in an agile development environment and collaborating through ticketing systems such as Jira and Azure DevOps.
Ability to communicate technical concepts clearly to technical and non-technical teams and influence decision-making.
Strong problem-solving skills with the ability to troubleshoot and resolve ambiguous, high-impact issues.
A results-oriented mindset with a demonstrated history of driving process improvements and technical excellence.
Ability to work independently while also serving as a trusted technical partner and mentor to others along
Ability to take vague requirements and turn them into technical roadmaps.

Responsibilities

Execute our cohesive data strategy that aligns with company objectives.
Lead the design, development, and evolution of Supplier.io data architecture, ensuring scalability, reliability, performance and security.
Execute and influence a cohesive data strategy that aligns with company objectives and supports analytics, reporting, and downstream product use cases.
Design, build, and maintain robust, cloud-native data pipelines and data warehouses, with Snowflake as a core component of the platform.
Own complex data modeling initiatives, including dimensional and analytical models that support business intelligence and advance analytics.
Evaluate, introduce, and integrate new tools, technologies, and methodologies, while aligning legacy counterparts for improved data ingestion, transformation, storage, and processing.
Drive continuous improvement by optimizing data pipelines, query performance, reliability, observability, and cost efficiency.
Partner with Infrastructure, Product, Analytics, and Engineering teams to ensure data systems meet best practices, security standards, and business needs.
Provide technical leadership and mentorship to other data engineers, contributing to code reviews, design discussions, and engineering standards.
Create and maintain comprehensive technical documentation, including architecture diagrams, data flow maps, runbooks, security considerations, and operations procedures.
Participate in agile planning and executive, contributing to estimation, prioritization, and delivery of high-impact data initiatives.
Troubleshoot and resolve complex, cross-system data issues and incidents.
Perform other duties as assigned.