Data Tech Lead | Canada

Cuesta Partners, LLC; Canada; Hybride; CAD 140 000 - 190 000; Plein temps

Résumé du poste

Cuesta Partners, LLC is seeking a Data Technical Lead in Canada to deliver end-to-end data solutions while mentoring a technical team. You will shape green-field data environments, establish best practices, and drive analytics initiatives for diverse client engagements.

The role emphasizes solving data challenges, architecting scalable data architectures, and guiding the team toward reusable data models and robust pipelines. Occasional US travel may be required.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 8–10 years experience as Data Engineer or similar role with design/implementation of data solutions.
• Active hands-on experience using AI-assisted development tools (Cursor, Claude Code, Codex or similar) in daily workflow.
• Proficiency in data modeling, ETL processes, and data integration.
• Experience with data warehousing and cloud platforms (AWS, Azure, GCP) and tools (SQL, Python, Spark).
• Strong leadership and team management skills with ability to guide a technical team.
• Excellent problem-solving and critical-thinking abilities.
• Effective communication with clients and stakeholders.

Responsabilités

• Act as subject matter expert in data engineering, resolving challenges and optimizing performance.
• Lead architectural discussions and trade-offs for data solutions.
• Set standards for AI-augmented development practices and coach the team.
• Lead planning, execution, and delivery of client-facing and internal data projects.
• Collaborate with Data Scientists, Analysts, and Stakeholders for seamless execution.
• Work with Team Lead to define data technology strategy and roadmap.
• Serve as data architect for client engagements and scalable solutions.
• Foster collaborative and inclusive team culture with knowledge sharing.
• Identify opportunities to improve processes, tools, and methodologies.

Connaissances

Data modeling

ETL processes

SQL

Python

Cloud platforms

Team leadership

Communication

Data architecture

Formation

Bachelor’s or Master’s degree in Computer Science or related field

Outils

Databricks

Snowflake

Microsoft Fabric

Description du poste

Cuesta Partners is looking for a Data Technical Lead in Canada with an interest in consulting, to work with our broad base of clients on various engagements, delivering data environments quickly using modern technologies and best practices, while mentoring others.

As a member of our data practice, you will have the unique opportunity to shape and build various green field areas, making a lasting impact on our clients’ data landscape. Collaborating closely with leadership, you will play a key role in establishing technology best practices to deliver analytical insights for customers in strategic domains. Your mission will be to deliver end-to-end data solutions, leveraging your expertise to unlock valuable insights and drive actionable decisions. As the driving force behind the acquisition and transformation of data sets, your contribution will be key to unlocking analytics insights from our client’s data. You will ensure that data models are reusable, data pipelines are scalable, and data visualizations are impactful. Your expertise in choosing, developing and optimizing data technology environments will be instrumental in driving our data-driven initiatives forward. This role ensures that development follows standards, specifications, controls, audits, and procedures to ensure data integrity, quality, accuracy, usefulness, and timeliness. While the role is remote, occasional though infrequent travel to the United States may be required for some critical sessions.

What We’re Looking For:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.




• Proven 8-10 years experience as a Data Engineer or similar role, with a strong background in designing and implementing data solutions.




• Active, hands‑on experience using AI-assisted development tools (e.g., Cursor, Claude Code, Codex, or similar) in your daily workflow — including building working prototypes, agentic pipelines, RAG systems, or LLM-powered data and analytics products — is a strong asset.




• Proficiency in data modeling, ETL processes, and data integration.




• Experience with modern data platforms such as Databricks, Snowflake, and Microsoft Fabric is a plus.




• Experience with data warehousing solutions, cloud platforms (e.g., AWS, Azure, GCP), and relevant tools (e.g.,SQL, Python, Spark).




• Strong leadership and team management skills, with the ability to inspire and guide a technical team.




• Excellent problem-solving and critical-thinking abilities.




• Effective communication skills, both technical and non-technical, with the ability to interact with clients and stakeholders.




• Adept at balancing technical requirements with business goals and client needs.

What You’ll Do

• Act as a subject matter expert in data engineering, providing guidance and hands‑on support to resolve technical challenges and optimize performance.




• Lead architectural discussions, providing insights into design decisions and trade-offs.




• Set the standard for AI-augmented development practices — ensuring projects are structured and tooled in ways that allow coding agents to operate effectively, and coaching the team to work the same way.




• Lead the planning, execution, and delivery of client‑facing and internal data projects, ensuring adherence to project timelines, scope, and quality standards.




• Collaborate with cross‑functional teams, including Data Scientists, Analysts, and Business Stakeholders, to ensure seamless project execution.




• Collaborate closely with the Team Lead to define the technology strategy and roadmap for the Data Team.




• Serve as a data architect for client engagements, working closely with clients to understand their data requirements, design appropriate data architectures, and develop scalable solutions.




• Foster a collaborative and inclusive team culture, promoting knowledge sharing and continuous learning among team members.




• Identify opportunities to improve processes, tools, and methodologies, driving efficiency and innovation within the Data Team.