Analytics Engineer

Ciklum • Canada,

21h • Remote

About The Position

As an Analytics Engineer, you will be at the forefront of transforming raw data into reliable enterprise data assets that enable strategic decision-making across the organization. Your focus will be building and productionalizing new Subscriptions data sets from the ground up, ensuring they support universal analytics needs for critical aspects of the business. You will collaborate closely with stakeholders to understand business needs, translate domain expertise into actionable data logic, and help shape the future of data-driven insights at scale. This role requires deep technical expertise in analytics engineering, a keen understanding of stakeholder needs, and the ability to drive alignment on data sets that serve as the single source of truth. You will support the creation and initial operationalization of data pipelines, while ensuring smooth transitions to long-term ownership by data engineering teams.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, Analytics, or a related field
• 4+ years of experience in data engineering, analytics engineering, or related fields, with a proven track record of building and maintaining large-scale data assets
• Expertise in SQL for querying and data transformation
• Strong programming skills in Python for data manipulation, automation, and building data pipelines. Experience with frameworks like Pandas, NumPy, and PySpark is preferred
• Experience with cloud data platforms such as Snowflake, BigQuery, or AWS Redshift, including working with cloud-native tools for data integration and transformation
• Experience with ETL orchestration tools such as Airflow for managing and scheduling DAGs, ensuring that workflows are efficient, reliable, and scalable
• Familiarity with data modeling concepts such as star/snowflake schemas and building logical and physical data models for analytics use cases
• Experience working with version control systems like Git for collaboration and maintaining code integrity
• Proficiency with BI tools such as Tableau, Looker, or Power BI for dashboarding and data visualization
• Experience with alerting and monitoring tools like Datadog, PagerDuty, or Grafana for ensuring data pipeline health and resolving issues proactively.
• Familiarity with CI/CD pipelines and experience with DevOps practices in a data engineering context
• Experience working with data governance and data quality frameworks to ensure compliance and accuracy of enterprise data
• Strong understanding of analytics workflows, from data collection to processing and analysis, with experience in data lineage and data cataloging tools (e.g., Alation, Collibra)
• Excellent problem-solving and communication skills, with the ability to navigate complex business needs and translate them into technical requirements

Nice To Haves

• Experience in the healthcare, health-tech, or similar industries, with exposure to working with healthcare data (e.g., claims, EHR, or HCP data)
• Familiarity with agile development methodologies and working in cross-functional teams
• Prior experience working with diverse data types, including event data, transactional data, and marketing data

Responsibilities

• Build Enterprise Data Assets (0 → 1): Lead efforts to create new data sets from scratch, focusing on foundational analytics assets that serve universal business purposes
• Enable Robust & Extensible Analytics: Establish widely accepted logic for critical data sets, driving alignment on a single source of truth that reduces confusion, rework, and analytical overhead
• Set Analytics Requirements: Collaborate with business stakeholders to capture data requirements, ensuring that new data assets are both fit for purpose and future-proof
• Translate Domain Expertise into Data Logic: Work with domain experts to convert their knowledge into computational logic that underpins new data sets
• Productionalize Data Sets: Build and deploy v1 data sets in a way that allows the business to benefit immediately from their insights, while ensuring scalability and maintainability
• Alerting & Monitoring: Implement alerting mechanisms to ensure that data sets are monitored effectively, with issues flagged to appropriate teams for timely resolution
• External Reporting Support: Enable data exports to external parties by supporting development and testing of reporting data sets
• Change Management Support: Help stakeholders manage changes to business logic and analytics requirements, especially when upstream data sets evolve (e.g., claim rewrite, coupon migration)

Benefits

• Healthcare
• Basic Life Insurance
• Short and Long-term disability insurance according to the Company’s Benefit Plans
• Udemy access
• language courses
• company-paid certifications

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level