Data Engineer

Company DescriptionThe Klick Group—comprising Klick Health (including Klick Katalyst and btwelve), Klick Media Group, Klick Applied Sciences (including Klick Labs), Klick Consulting, and Klick Ventures—is an ecosystem dedicated to realizing the full potential of our people and clients in life sciences. Founded in 1997, we have offices in New York, Philadelphia, Saratoga Springs, Toronto, London, São Paulo, and Singapore. Consistently named a Best Managed Company, Most Admired Corporate Culture, and Great Place to Work, Klick is committed to fostering a high-performance, people-first culture with creativity, collaboration, innovation, and impact across everything we do.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, platforms, and analytics, the craft supports seamless journeys and measurable outcomes. Their work enhances effectiveness, optimization, and insight across the ecosystem.Job DescriptionThe Data Engineer supports analytics and omnichannel initiatives by designing, building, and maintaining data infrastructure and pipelines that enable scalable, data-driven outcomes. This role works closely with Analytics, Data Science, and Enablement partners to translate requirements into reliable, high-quality data solutions. The focus is on engineering rigor, platform performance, and delivering the data foundation that powers insights across teams and clients.What You’ll DoCollaborate with Analytics, Data Science, and Enablement partners to gather requirements and translate business needs into data engineering solutions using Python and SQLDesign, build, and maintain ETL pipelines and ingestion notebooks to move and transform data across systemsWork extensively in Microsoft Fabric to develop and manage data workflows and infrastructureWrite and optimize SQL queries for performance, troubleshooting, and data investigationInvestigate and resolve data issues in databases using SQL, identifying root causes and implementing fixesBuild scalable PySpark-based solutions for large-scale data processing and transformationDevelop a strong understanding of system architecture and data flows to support reliable pipeline operationsQualificationsRequired:Strong SQL proficiency — query writing, optimization, and database investigation are core to this roleHands-on experience building and maintaining ETL pipelines and data ingestion workflowsWorking knowledge of PySpark for large-scale data processingExperience with Microsoft Fabric or similar modern data platformsSolid understanding of end-to-end system architecture and how data moves through itExperience translating technical concepts for non-technical stakeholders, including gathering requirements from clients or business partnersDesired:Comfort and enthusiasm for using AI as a regular part of how work gets doneExperience in healthcare, life sciences, media, or agency environments, including marketing or payer analytics datasetsExperience working with advertising APIs (e.g. Google Ads, Meta, or similar platforms)Advanced degree (Master’s or Ph.D.) in Computer Science, Data Engineering, Data Science, or a related quantitative fieldKnowledge of database design and data modeling principles within modern analytics platformsExperience with data visualization tools such as Power BIFamiliarity with CI/CD pipelines or Git-based version controlAdditional InformationThis posting is for an existing vacancy at Klick. The base salary range for this position is between CAD $85,000 - $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. #LI-TH1 #LI-HybridOur 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 [email protected] and we will work with you to meet your accessibility needs and ensure you have a positive experience.

The Data Engineer designs, builds, and maintains data infrastructure and ETL pipelines to support analytics and omnichannel initiatives. They collaborate with cross-functional partners to translate business requirements into scalable, high-quality data solutions.

Candidates must have strong proficiency in SQL, PySpark, and experience with modern data platforms like Microsoft Fabric. Ability to translate technical concepts for non-technical stakeholders and a solid understanding of end-to-end system architecture are required.

Identified from the job description. Confirm important requirements above.

• SQL
• Python
• PySpark
• Microsoft Fabric
• ETL Pipelines
• Data Ingestion
• System Architecture
• Data Modeling
• Power BI
• CI/CD
• Git
• Data Transformation

• Data & Analytics
• Technology
• Engineering
• Healthcare
• Consulting

Minimum education

Master’s degree

Minimum experience

2+ years

Posting language

English

Working hours

40 hours per week