Senior Data Architect modernizing Alberta justice data marts into an integrated enterprise data warehouse. Designing ETL, Power BI testing, data models, governance, and reporting architecture.
About the role
- Senior Data Engineer at DraftKings designing and scaling modern data infrastructure for analytics. Collaborating with cross-functional teams to solve technical problems and drive innovation.
Responsibilities
- Build scalable, high-performance data infrastructure that transforms raw and historical data into trusted, actionable insights.
- Design, develop, and maintain real-time and batch data pipelines using technologies such as Kafka, Databricks, and Snowflake.
- Develop reliable data solutions that power business-critical reporting, analytics, and platform insights.
- Build AI-powered data experiences that enable teammates to explore and analyze data using natural language, extending beyond text-to-SQL to support intelligent, autonomous workflows.
- Partner with Engineering, Analytics, and cross-functional stakeholders to translate complex business requirements into scalable, analytics-ready datasets.
- Design and optimize modern data models, including Star Schema and Data Vault methodologies, while championing data quality, governance, and observability.
- Drive best practices for data engineering, streaming, transformation, and platform performance while mentoring teammates and contributing to the continued growth of the Data Engineering Team.
- Collaborate in an agile environment, delivering scalable solutions that support evolving business and platform needs.
Requirements
- A Bachelor's Degree in Computer Science or a related field, or an equivalent combination of education, training, and professional experience.
- At least 3 years of experience designing, building, and maintaining scalable data platforms and distributed data systems.
- Strong proficiency in Python and SQL, with hands-on experience building real-time data streaming solutions.
- Experience working with Snowflake, Databricks, Kafka, and modern cloud-based data platforms.
- Experience with cloud infrastructure, preferably Amazon Web Services (AWS), and familiarity with infrastructure and DevOps tools such as Terraform, PagerDuty, and Datadog.
- Deep understanding of data warehousing, data lakes, ETL frameworks, and modern data modeling techniques, including Star Schema and Data Vault.
- Experience working with NoSQL databases such as MongoDB or DynamoDB; familiarity with Sigma or similar business intelligence tools is a plus.
- Hands-on experience using AI-assisted engineering tools such as Claude Code, Codex, or similar technologies to build agents, automate workflows, and accelerate software development.
- Strong communication and collaboration skills, with the ability to thrive in a fast-paced, cross-functional environment while mentoring and supporting other engineers.
Benefits
- Health insurance
- Retirement plans
- Paid time off
- Flexible work arrangements
- Professional development
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