Senior Data Platform Developer

Helcim Inc•Calgary, AB

2d•Hybrid

About The Position

Helcim is searching for a Senior Data Platform Developer to help lead the design, development, and ongoing evolution of the data platform that powers Helcim’s mission to become the world’s most loved payments company. As a senior individual contributor within Helcim’s data centre of excellence, you will be a go-to technical expert for our data platform. You’ll work hands-on across our data infrastructure, MLOps/AI tooling, governance practices, and real-time modeling and monitoring capabilities, while establishing the standards that ensure our data platform is scalable, trusted, and highly accessible. At this level, we’re looking for someone who can take undefined business and technical problems, break them down into clear milestones, and lead the work through to high-quality outcomes. Collaborating cross-functionally, you will influence key architectural decisions, mentor data professionals across the Data Platform & Science teams, and proactively mitigate platform risks before they scale. You are an experienced data professional who thrives on solving complex, real-world problems and building resilient, scalable systems that last. Comfortable operating in ambiguity, you know how to ask the right questions and drive deep technical solutions that serve long-term business goals. While you love being hands-on, you are also a natural team multiplier who elevates those around you through active mentorship, clear documentation, and technical leadership. You care deeply about technical excellence but understand how to balance speed with long-term quality, making pragmatic architectural tradeoffs that scale with the business. Ultimately, you are energized by the opportunity to shape the future of Helcim’s data platform and empower teams across the company to do their best work.

Requirements

6+ years of experience as a data engineer, analytics engineer, data platform developer, or similar role.
Strong experience designing, building, and maintaining production-grade data pipelines and data platform infrastructure.
Experience deploying data products, analytics assets, or data platform capabilities into production.
Experience working cross-functionally with technical and non-technical stakeholders to understand business needs and translate them into scalable technical solutions.
Demonstrated experience leading complex technical projects from discovery through delivery.
Experience mentoring, coaching, reviewing work, or otherwise helping other team members grow technically.
You excel at untangling vague, complex data problems, distilling them into practical, high-quality execution plans while creating clarity for the broader team.
You possess strong technical judgment and make sound cross-domain trade-offs. You proactively hunt down platform risks, technical debt, and governance gaps before they scale.
You naturally multiply the effectiveness of the engineers around you through collaborative technical guidance, code reviews, and robust documentation.
You can effectively drive buy-in for platform roadmaps and confidently represent technical decisions to both internal leadership and external entities (e.g., auditors or compliance).

Nice To Haves

BigQuery, dbt, Airflow, and Airbyte as our data warehousing technologies
SQL + Python as our programming languages
Experience developing Agentic Workflows
Experience developing Specs/Skills for IDEs to automate the development of data pipelines & infrastructure
Hands-on experience with Kubernetes for deploying, scaling, and managing containerized data applications and MLOps workflows.

Responsibilities

Drive and own the advancement of Helcim’s MLOps and AI Gateway infrastructure, actively pushing these capabilities forward to support production AI and machine learning models.
Lead the end-to-end design of scalable data pipelines (structured and semi-structured) to power ML models, AI systems, BI, and operational decision needs.
Continually improve Helcim’s self-managed data platform for high performance, reliability, and observability, while proactively mitigating technical risks.
Expand internal AI tooling and automate data governance to ensure data quality, privacy, security, and trust.
Translate ambiguous data platform challenges into clear technical milestones, execution plans, and long-term roadmap contributions.
Partner with the Staff Developer to drive technical design, balancing trade-offs and advising on complex cross-team data platforms.
Foster a collaborative data culture by mentoring engineers (co-designing, code reviews) and equipping teams with the data tools and documentation they need to succeed.