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- Employment type
- Full-time
- Experience level
- Lead · 10+ years
- Posting language
- English
- Working hours
- 40 hours per week
- Location requirements
- Country, Calgary, Alberta, Canada
- Seniority
- Director
Job summary
Own the technical direction and architecture of data engineering initiatives, designing and building scalable, production-grade pipelines with Databricks, PySpark, AWS, and SQL. Lead hands-on development and technical decisions, mentor engineers, guide architectural trade-offs, and collaborate with product, data, and engineering stakeholders.
Job details
What We’re Building We partner with global enterprises to design and scale data platforms that power products used by millions of users. Our work involves large-scale data systems, complex pipelines, and high-impact business use cases across multiple industries. This role focuses on technical leadership, architectural ownership, and mentoring while remaining hands-on. Your Role as a Tech Lead As a Tech Lead, Data Engineering, you will own the technical direction of data initiatives while remaining hands-on. You’ll act as the bridge between architecture, execution, and people leadership. What You’ll Do Own the technical direction and architecture of data engineering projects Design and build scalable, production-grade data pipelines using Databricks, PySpark, AWS, and SQL Lead by example with hands-on development, code reviews, and technical decision-making Mentor and guide data engineers, promoting best practices, clean code, and high engineering standards Drive architectural discussions, trade-offs, and long-term technical vision Collaborate closely with product, data, and engineering stakeholders Tackle enterprise-scale data challenges with real-world business impact business outcomes What We’re Looking For 10+ years of experience in Data Engineering or related roles Proven experience as a Tech Lead, Lead Data Engineer, or similar role Strong hands-on expertise with: Python & SQL, PySpark, Databricks and AWS Solid background in data architecture, pipeline design, and distributed systems Experience mentoring engineers and leading technical initiatives Strong communication skills and the ability to influence technical decisions Fluent in English (spoken and written) Salary Salary range: CA$90,000 - CA$181,000 annually, with final compensation determined by your qualifications, expertise, experience, and the role's scope. Location: This is a fully remote position; however, candidates must be based in regions that align with the Pacific, Central, or Eastern U.S. time zones to ensure effective collaboration with client and team schedules. Benefits In addition to competitive pay, we offer a variety of benefits to support your professional and personal growth, including: Flexible working hours in a remote environment. Health insurance (medical and dental) for T4 Employees. A professional development fund to enhance your skills and knowledge. 15 days of paid time off annually. Access to soft-skill development courses to further your career. Position Details This is a full-time position requiring a minimum of 40 hours per week, Monday through Friday. Application Deadline Applications will be accepted until October 25th, 2026. Candidates can expect feedback by November 2nd, 2026.
What you’ll do
Own the technical direction and architecture of data engineering initiatives, designing and building scalable, production-grade pipelines with Databricks, PySpark, AWS, and SQL. Lead hands-on development and technical decisions, mentor engineers, guide architectural trade-offs, and collaborate with product, data, and engineering stakeholders.
Requirements
Requires 10+ years of experience in data engineering or a related field, with proven experience as a tech lead or lead data engineer. Candidates need strong hands-on expertise in Python, SQL, PySpark, Databricks, and AWS, along with data architecture and distributed systems experience, mentoring ability, strong communication skills, and fluency in English.
Benefits
- Flexible Working Hours
- Health Insurance
- Dental Insurance
- Professional Development Fund
- 15 Days Of Paid Time Off
- Soft-Skill Development Courses
Listed skills
- SQL · Preferred
- Communication · Preferred
- Amazon Web Services · Preferred
- Python · Preferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Data Engineering
- Technical Leadership
- Python
- SQL
- PySpark
- Databricks
- AWS
- Data Architecture
- Data Pipeline Design
- Distributed Systems
- Code Reviews
- Mentoring
- Technical Decision-Making
- Stakeholder Collaboration
- Communication
Job areas
- Data & Analytics
- Technology
- Software
- Management & Leadership
- Consulting
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