Senior Data Engineer - Data Analytics & BI

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer – Data Analytics & BI based in Canada. This role is responsible for building and optimizing scalable data infrastructure and analytics solutions that support data-driven decision-making across the organization. You will work across data engineering, business intelligence, reporting, and analytics to turn complex datasets into actionable insights. The position combines hands-on development with close collaboration across Data Engineering, Data Science, and business teams. You will design reliable ETL/ELT pipelines, develop self-service dashboards, and improve data quality and accessibility. The role offers an opportunity to influence how teams use data while applying strong engineering, documentation, testing, and performance practices. You will also contribute to a collaborative environment focused on continuous learning, innovation, and technical excellence. Accountabilities - Triage requests for people data, reporting, and ad hoc analysis, prioritize work, and communicate realistic delivery expectations to stakeholders. - Design, develop, automate, and maintain scalable ETL/ELT pipelines that ingest, transform, validate, and deliver data from diverse internal and external sources. - Build self-service reports, dashboards, and data visualizations that communicate meaningful KPIs and enable leaders to identify insights and make informed decisions. - Partner with stakeholders to define reporting requirements and continuously improve core dashboards, analytics solutions, and data products. - Use SQL, Python, Tableau, Jupyter Notebook, and related technologies to extract, organize, analyze, and visualize data from multiple sources. - Collaborate with Data Engineering, Data Science, and other cross-functional teams to apply effective practices in data collection, pipeline architecture, analytics, and solution development.

- Audit data integrity, investigate data-quality issues, and establish processes that improve the accuracy, consistency, and reliability of reporting and analytics. - Optimize ETL processes through effective architecture, code optimization, and performance improvements. - Provide guidance and coaching to end users on interpreting metrics, using dashboards, and applying data effectively. - Document reporting requirements, technical designs, data definitions, operational procedures, and changes to analytics solutions. - Participate in on-call responsibilities, monitoring data systems and responding to operational issues to maintain reliability and uptime. - Stay current with emerging data engineering practices, analytics technologies, cloud platforms, and industry trends. Requirements: - 8+ years of professional experience with SQL, including complex query optimization and large-scale relational and columnar databases. - 5+ years of hands-on Python experience focused on data engineering, including pipeline development, automation, and data transformation. - 8+ years of experience developing custom reports, dashboards, and visualizations using Tableau or comparable business intelligence tools. - Strong experience with data management, including validating, auditing, and reconciling data and reports across multiple systems. - Hands-on experience with cloud-based data platforms such as AWS, Azure, or Google Cloud Platform, as well as distributed technologies such as Spark or Hadoop. - Strong knowledge of relational database systems and familiarity with NoSQL technologies such as MongoDB or Cassandra. - Experience with data orchestration and transformation tools such as Apache Airflow and dbt. - Experience with Apache Hive and Presto for large-scale distributed query processing.