123Dentist is Canada’s largest majority dentist-owned network of dental practices, with almost 500 locations nationwide and nearly 8,000 employees. We offer professional advancement opportunities, competitive compensation, corporate sponsored incentive programs such as long-term bonuses for full-time employees (a first of its kind in the Canadian dental industry), and a long-term career in a growing network located in multiple communities across the country, at all levels of the industry.
Whether you’re entering the job market or you’re an experienced practitioner, we welcome your interest! Come join the 123Dentist team and be part of our success.
We provide Canadian dentists and dental practices with an array of non-clinical support and resources, including accounting, HR, marketing, as well as supply & equipment procurement.
By leveraging our unmatched management experience, marketing expertise and state-of-the-art technologies, we allow dentists to take advantage of a practical and effective alternative to practice ownership and focus on what they’re best at – being a dentist!

JOB OVERVIEW:

We are seeking an experienced Senior Data Engineer to join our data team, responsible for leading, designing, building, and maintaining robust data pipelines and infrastructure. The ideal candidate will have deep expertise in modern data integration and transformation tools to support our data-driven decision-making processes. The candidate will collaborate with cross-functional teams to ensure data availability, reliability, and scalability while optimizing our data workflows.

EDUCATION, CREDENTIALS, QUALIFICATIONS:

• Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience).
• 7+ years of relevant experience in Data Engineering / Analytics domain with at least 3 years in Digital Analytics
• 7+ years of experience in SQL and 4+ years in Python
• 3+ years of experience in data analysis, data modeling and data management
• Proven expertise with ADF, Qlik Replicate, FiveTran for data integration and ETL processes.
• Strong understanding of Python scripting and use of libraries (NumPy, Pandas)
• Extensive hands-on experience with MS Fabric, including data warehousing, SQL optimization, and cluster management.
• Strong knowledge of Big Data technologies such as Data Bricks, Event driven data processing using Function Apps/Lambda is preferred
• Understanding of Web services (SOAP, XML, UDDI, WSDL)
• Strong knowledge and experience in event driven architecture using standard message queues (i.e.RabbitMQ, SQS or Kafka)
• Experience with building a data lake over Cloud / Azure, ADF, Synapse, and Databricks – Delta Lake
• Hands on Experience parsing NOSQL file systems such as JSON, XML, AVRO, Parquet.
• Proven track record of using Apache Spark Data Bricks.
• Hands-on experience with Azure Data Factory (ADF), Logic Apps, and Runbooks.
• Exposure to traditional BI Tools (Tableau, Power BI, Qlik, SSRS, etc.)
• Experience building web-services is a plus.

REQUIRED SKILLS & ABILITIES:

• Solid understanding of data pipeline architecture, cloud infrastructure, and best practices in data engineering.
• Excellent problem-solving skills and attention to detail.
• Ability to work independently and collaborate effectively in a team environment.
• Skilled in independently analyzing large datasets, identifying discrepancies and inconsistencies, and recommending corrective actions.
• Strong problem-solving and analytical skills.
• Excellent communication and teamwork abilities, with experience engaging stakeholders at all levels.
• Self-starter. Proven ability to manage multiple, concurrent projects with minimal supervision. Can manage a complex ever changing priority list and resolve conflicts to competing priorities.

• Support the enhancement of data lake platforms acquiring additional data sources - structured and unstructured
• Develop highly scalable and extensible Big Data platform which enables collection, storage, modeling, and analysis of massive data sets from numerous channels
• Be an active part in analyzing and constantly learning the latest Big Data technologies and their innovative applications in both business intelligence analysis and new service offerings, adopt and implement these insights and best practices
• Participate in project planning by collaborating with business analysts and data team to understand data requirements and deliver high-quality datasets.
• Drive projects that merge digital and transactional data for advanced analytics.
• Mentor and provide technical guidance to data engineers, report developers, and analysts.
• Optimize and tune data warehouse performance, including schema design, indexing, and query optimization.
• Act as a technical leader for the team, establishing best practices for data engineering.
• Ensure data integrity, security, and compliance with best practices throughout the data lifecycle.
• Implement robust data validation and quality assurance processes to maintain high data integrity.