Embracing a growth mindset where curiosity thrives, we celebrate excellence and value individuals who inspire and mentor others, elevating the collective. Our driving force lies in personal and business growth. We go above and beyond to surprise and delight our clients, delivering tangible business value. In facing challenges, we make tough choices and solve complex problems to positively influence our clients, their customers, and the world at large.
As a Microsoft services partner, we hold ourselves to the highest standards of technical excellence. This commitment to quality is evident not only in our work but also in how we support and empower our employees. At Lantern, our culture mirrors our core values and unwavering dedication to realizing our purpose and vision, making it a dynamic and fulfilling workplace. Together, we transcend the ordinary and achieve extraordinary results.
Position Summary
We are seeking a Senior or Principal Data Engineer to design, build, and optimize data platforms on Amazon Web Services. This is a hands-on, AWS-native engineering role for someone who lives in the details of large-scale analytical data: tuning Redshift and Athena, writing production Python, and squeezing performance out of queries that run against multi-terabyte datasets. You'll own the architecture and reliability of data pipelines end to end, set the standard for engineering quality, and mentor others on what great looks like in a modern AWS data environment.
This role is based on-site in Edmonton. Relocation support is available for the right candidate.
Position Responsibilities
Design, build, and maintain scalable, secure, and performant data pipelines on AWS, with Redshift and Athena at the core of the analytical platform.
Optimize query and warehouse performance on very large datasets (multi-TB tables) through distribution and sort key design, partitioning strategy, file/format optimization, and scan-cost reduction.
Develop robust, production-grade ETL/ELT in Python, with strong attention to testing, error handling, retries, and observability.
Package and deploy data workloads using Docker and containers.
Apply data engineering fundamentals — modeling, data quality, lineage, and reliability — to deliver trustworthy data for analytics and downstream consumers.
Collaborate with stakeholders to translate data needs into well-architected, maintainable solutions.
Set engineering standards and mentor team members, promoting best practices across the AWS data stack (Principal-level scope).
Stay current with the AWS data ecosystem and bring forward improvements in performance, cost, and developer productivity.
Qualifications
Bachelor's degree in Computer Science, Data Engineering, or a related discipline, or equivalent practical experience.
Senior: 5+ years / Principal: 8+ years of hands-on data engineering experience, with significant time spent building on AWS.
Strong production Python for data pipelines and automation.
Demonstrated, in-depth experience with Amazon Redshift and Amazon Athena, including real-world performance and cost optimization.
Proven track record optimizing queries and pipelines on large datasets (multi-terabyte scale) — you can speak to specific before/after wins.
Working experience with Docker / containers as part of your build and deployment workflow.
Solid data engineering fundamentals: data modeling, warehouse/lakehouse design, partitioning, and data quality.
Excellent communication and collaboration skills, with the ability to explain technical trade-offs to varied audiences.
Preferred Qualifications
Experience with AWS CDK (infrastructure as code) and IAM least-privilege design.
Experience with ECS, AWS Step Functions, and AWS Lambda for orchestration and serverless data workloads.
Familiarity with AI-assisted development tools and workflows.
AWS certifications such as AWS Certified Data Engineer – Associate or AWS Certified Solutions Architect.
Benefits
A culture that both wows our customers and employees;
Variety of challenging projects, and the ability to work with leading-edge technologies;
Competitive salary & group benefits;
Generous training and education opportunities;
Diverse team social events;
Be part of a team that believes in diversity, inclusion, and a fun atmosphere!
Lantern is committed to fair and equitable compensation practices. Actual compensation will depend upon an individual's skills, experience, qualifications, location, and other relevant factors. The salary pay range is subject to change and may be modified at any time.
Skills Required
- Bachelor's degree in Computer Science, Data Engineering, or related discipline or equivalent experience
- 5+ years (Senior) or 8+ years (Principal) hands-on data engineering experience with significant AWS experience
- Strong production Python for data pipelines and automation
- In-depth experience with Amazon Redshift and Amazon Athena, including performance and cost optimization
- Proven track record optimizing queries and pipelines on multi-terabyte datasets
- Working experience with Docker and containers for build and deployment
- Solid data engineering fundamentals: modeling, warehouse/lakehouse design, partitioning, data quality, lineage, reliability
- Excellent communication and collaboration skills
- Experience with AWS CDK and IAM least-privilege design
- Experience with ECS, AWS Step Functions, and AWS Lambda for orchestration and serverless workloads
- Familiarity with AI-assisted development tools and workflows
- AWS certifications (e.g., AWS Certified Data Engineer - Associate or AWS Solutions Architect)
What We Do
In the digital economy, success belongs to those who can harness the power of AI to drive innovation, efficiency, and growth. Lantern is here to guide you through this transformative journey to digital leadership. As a premier IT professional services firm, we specialize in helping organizations envision, implement, and run Microsoft technologies to achieve AI excellence.
