Senior Data Solutions Consultant
- Toronto, ON, Canada
The base salary range for this position is between CAD $90,000 - $105,000. · Full-time
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Job details
- Pay
- The base salary range for this position is between CAD $90,000 - $105,000.
- Job type
- Full-time
- Apply by
- Experience
- 4–5 years of hands-on experience developing scalable data solutions, designing and supporting ETL pipelines for analytics and reporting.
- Posting language
- English
- Posted
Original job description
About Our Omnichannel Enablement Craft
Our Omnichannel Enablement Craft connects channels, data, and technology into unified experiences. The team ensures audiences encounter consistent, coordinated messaging across touchpoints. By aligning media and platforms, they support seamless journeys. Their work enhances effectiveness and measurement across the ecosystem.
Job Description
The Senior Data Solutions Consultant partners with cross-functional teams to design, build, and optimize scalable data solutions that support omnichannel marketing, analytics, and AI-enabled products for life sciences clients. This role collaborates closely with analytics, engineering, project management, and client stakeholders to transform complex datasets into reliable, production-ready data assets that drive measurable business outcomes. Success in this role requires expertise in Python, SQL, ETL development, enterprise data platforms, and modern business intelligence technologies.
What You'll Do
- Build analytics products including business intelligence dashboards, system integrations, data outputs, presentations, and AI-enabled solutions using platforms such as Power BI, Microsoft Fabric, and Tableau.
- Develop, maintain, and optimize enterprise data warehouse solutions, preferably in Snowflake, while ensuring data quality, reliability, scalability, and performance.
- Design, develop, and optimize scalable ETL pipelines using Python and SQL to support analytics, reporting, AI solutions, and client deliverables.
- Collaborate with data analysts, project managers, business analysts, and client stakeholders to gather technical requirements, define solution architecture, and deliver measurable business outcomes.
- Standardize and improve engineering practices through reusable code, Git version control, documentation, SOP development, and scalable data engineering processes that support operational excellence.
Required:
- Experience using Python and SQL to build, optimize, and maintain production-ready data pipelines and data models.
- 4–5 years of hands-on experience developing scalable data solutions, designing and supporting ETL pipelines for analytics and reporting.
- Experience working with clickstream datasets, enterprise data lakes, and modern cloud data warehouse platforms, preferably Snowflake, supporting analytics or marketing use cases.
- Experience gathering technical requirements from business stakeholders and clients, translating business needs into production-ready data solutions and measurable deliverables.
- Experience developing business intelligence solutions using Power BI, Microsoft Fabric, Tableau, or comparable visualization platforms, with examples of dashboards or reporting solutions delivered.
- Comfort and enthusiasm for using AI as a regular part of how work gets done.
- Experience supporting healthcare, pharmaceutical, or life sciences data, analytics, or omnichannel marketing initiatives.
- Experience designing relational database structures, dimensional models, and enterprise data architecture supporting scalable analytics platforms.
- Bachelor's degree in Computer Science, Software Engineering, Data Engineering, or a related technical discipline.
- Experience implementing Git-based development workflows, documentation standards, and reusable engineering practices across collaborative technical teams.
This posting is for a new vacancy at Klick. The base salary range for this position is between CAD $90,000 - $105,000. The final amount offered will be determined based on several factors such as a candidate's work location, their unique skill set, education, and prior work experience.
Our Commitment to Inclusion
Klick is consciously creating a culture where everyone can thrive and grow in their careers. We believe that our best work comes from our diverse backgrounds, perspectives, and skills. We strongly encourage members of historically underrepresented communities to apply, including Black people, Indigenous peoples, and other people of color, people with disabilities, people from gender and sexually diverse communities and people with intersectional identities. We're also committed to developing an inclusive, barrier-free recruitment process and work environment. Should you require any accommodation, please contact us at careers@klick.com and we will work with you to meet your accessibility needs and ensure you have a positive experience.
Klick uses an AI-powered tool as part of an automated process to support our hiring process by analyzing your experience, skills, and qualifications to help identify alignment with role requirements. Please note that the tool does not make final decisions or automatically disqualify candidates. Hiring decisions are made by our team, with thoughtful human judgment and oversight. We are committed to fair and transparent hiring practices and have implemented safeguards to help mitigate bias and support compliance with applicable laws. If you have questions, accessibility needs, or concerns about the use of this tool, please contact us.
More about this job
Responsibilities
Build and optimize scalable data pipelines, enterprise data warehouse solutions, business intelligence products, integrations, and AI-enabled solutions for life sciences clients. Collaborate with technical teams and client stakeholders to define requirements, deliver measurable outcomes, and improve engineering practices through reusable code, version control, and documentation.
Requirements
Requires 4–5 years of hands-on experience building production-ready data solutions and ETL pipelines with Python and SQL, along with experience in clickstream data, enterprise data lakes, and cloud data warehouses such as Snowflake. Candidates should also have experience translating stakeholder requirements into deliverables and developing BI solutions; life sciences experience, data architecture expertise, a relevant bachelor's degree, and Git-based workflows are desired.
Skills
- Python
- SQL
- ETL Development
- Data Pipelines
- Data Modeling
- Snowflake
- Power BI
- Microsoft Fabric
- Tableau
- Data Warehousing
- Data Lakes
- Clickstream Data
- Business Intelligence
- Git
- Data Architecture
- Stakeholder Requirements Gathering
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Marketing
- Consulting
Keywords
- Python
- SQL
- ETL
- Data Pipelines
- Data Models
- Snowflake
- Power BI
- Microsoft Fabric
- Tableau
- Business Intelligence
- Enterprise Data Warehousing
- Enterprise Data Lakes
- Clickstream Data
- Data Quality
- Data Architecture
- Dimensional Modeling
- Relational Databases
- Git
- Version Control
- Data Engineering
- Analytics
- Omnichannel Marketing
- Life Sciences
- Healthcare Data
- AI-Enabled Solutions
- Cloud Data Platforms
- System Integrations
- Technical Requirements
- Reusable Code
- Standard Operating Procedures