Data Engineering Manager, Regulatory Compliance
New
J
JobgetherSports, betting, gaming
Based in United StatesFull-TimeManager
Salary165,000 - 200,000 CAD per year
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Job Details
- Experience
- At least 3 years of experience in a data-oriented leadership or management role combined with 5+ years of software or data development experience
- Required Skills
- AWSDockerPythonSQLAgileGCPAirflowdbt
Requirements
- At least 3 years of experience in a data-oriented leadership or management role.
- 5+ years of software or data development experience.
- Proven experience managing or leading teams of at least three engineers.
- Strong foundation in computer science, distributed systems, software engineering, system design, data architecture, and data governance.
- Experience working in a regulated industry or environment with compliance requirements and audits.
- Strong project management and prioritization skills using Atlassian and other Agile tools.
- Strong knowledge of relational databases, SQL, Python, and Docker.
- Experience with cloud platforms such as AWS or GCP and related services.
- Experience with data pipeline and workflow technologies such as Airflow, dbt, or AWS Lambda.
- Ability to communicate complex technical information clearly to non-technical audiences and regulatory professionals.
Responsibilities
- Lead the day-to-day activities of the data engineering team, including goal setting, mentorship, coaching, performance management, feedback, delegation, and technical guidance.
- Establish clear expectations and communicate professionally with state and provincial regulatory professionals.
- Partner with Analytics, Finance, Compliance, Product, Data Services, and other engineering teams to develop data pipelines, infrastructure, and tooling.
- Prioritize and manage data-related projects across functions, guiding initiatives from initial planning and requirements through delivery.
- Contribute to the design, maintenance, and continuous enhancement of data pipelines, architecture, infrastructure, and engineering processes.
- Ensure data engineering solutions meet appropriate standards for performance, scalability, reliability, data quality, and regulatory requirements.
- Communicate technical concepts, project status, risks, and priorities clearly to stakeholders.
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