Senior Data Developer, Analytics & Insights in Canada Creek, Nova Scotia at Jobgether
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Job Description
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 Developer, Analytics & Insights based in Canada.
This is a high-impact data engineering role focused on building and optimizing scalable data pipelines that power analytics, insights, and data-driven decision-making across enterprise platform initiatives.
You will design, develop, and maintain robust ELT/ETL pipelines handling large volumes of structured and unstructured data across modern cloud environments.
The role involves close collaboration with analysts, data scientists, product managers, and engineering teams to translate business needs into reliable and efficient data solutions.
You will play a key role in strengthening data architecture, improving pipeline performance, and ensuring data quality, governance, and integrity at scale.
A strong emphasis is placed on automation, innovation, and leveraging AI-native data engineering practices to enhance scalability and efficiency.
This position is ideal for an experienced data engineer who thrives in complex, cloud-based ecosystems and enjoys solving large-scale data challenges.
- Design, develop, automate, and maintain scalable ELT/ETL data pipelines that process large volumes of structured and unstructured data from multiple sources.
- Improve and maintain existing data architecture to ensure reliable, efficient, and secure data flow across platforms.
- Collaborate with data peers, product managers, and cross-functional stakeholders to gather requirements, define solutions, and document technical designs.
- Implement best practices for data quality, governance, monitoring, validation, and auditing to ensure trustworthy datasets.
- Optimize pipeline performance and resource efficiency using modern engineering and AI-native approaches, including anomaly detection and schema evolution.
- Work with big data technologies and frameworks to support large-scale analytical workloads.
- Contribute to continuous innovation by adopting emerging tools, technologies, and industry best practices in data engineering.
- Support integration of data pipelines with cloud infrastructure and analytics platforms to enable downstream insights and reporting.
- 5+ years of experience in data engineering or large-scale data processing within cloud-based environments, with strong AWS expertise.
- Strong programming skills in Python and advanced proficiency in SQL.
- Experience with data modeling, analytical data warehouses (e.g., Snowflake, Presto, Hive), and dimensional modeling techniques.
- Hands-on experience with data pipeline orchestration tools such as Airflow.
- Strong understanding of ETL/ELT processes and experience working with both traditional and modern data engineering frameworks.
- Familiarity with big data technologies such as Spark and Hadoop.
- Experience handling semi-structured data formats such as JSON and Parquet.
- Knowledge of AWS services (e.g., Glue, Lambda, EMR, EKS) and cloud-based data architecture.
- Exposure to infrastructure-as-code and automation tools such as Terraform, Git, and Jenkins is an asset.
- Strong communication, collaboration, and problem-solving skills in a fast-paced environment.
- Nice to have: experience with DBT, Spark SQL, REST APIs, containerization, and AI-native data engineering concepts (MCP, context engineering, agentic workflows).
- Competitive compensation package with performance-based incentives and equity opportunities.
- Comprehensive health, dental, and vision insurance coverage.
- Flexible work arrangements, including remote options across Canada.
- Opportunity to work on large-scale, cutting-edge data platforms and cloud-native architectures.
- Exposure to advanced analytics, AI-driven data engineering, and emerging technologies.
- Strong focus on learning, innovation, and professional development.
- Inclusive, collaborative environment within a global technology organization.