Senior Manager, Data Engineering – Analytics

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead and cultivate a small global team specializing in data engineering, analytics, and business intelligence.

• Take charge of the architecture, reliability, and progressive development of the analytical data platform.

• Design and construct scalable batch and event-driven pipelines that encompass clinical, operational, product, financial, and customer data.

• Implement data-quality practices involving testing, monitoring, lineage, reconciliation, alerting, and incident response.

• Establish trusted metrics, dimensional models, curated datasets, and semantic layers.

• Provide dashboards, recurring reports, customer reporting, self-service datasets, and actionable insights.

• Collaborate with clinical, operations, product, finance, engineering, and commercial stakeholders.

• Lead discussions with customers regarding reporting requirements, metric definitions, discrepancies, and data delivery challenges.

• Analyze complex data issues, pinpoint root causes, and implement sustainable solutions.

• Enhance platform performance, cost-effectiveness, security, privacy, and maintainability.

• Prioritize tasks, review technical work, mentor team members, and support organizational scalability.

• Build and maintain pipelines utilizing AWS Glue, Lambda, SNS, S3, PySpark, and Amazon Redshift.

• Create and uphold dbt models, Airflow workflows, data tests, and monitoring systems.

• Design dimensional models, star schemas, and curated analytical layers.

• Utilize SQL and Python to explore data, validate outcomes, and resolve production issues.

• Develop and assess dashboards and reports in Sigma, Looker, or other similar BI tools.

• Convert unclear business and customer requirements into scalable data solutions.

• Guide business inquiries from discovery through metric definition, analysis, visualization, and recommendation.

• Review architecture, code, data models, dashboards, and analytical methodologies.

• Convey findings, risks, limitations, and recommendations to both technical and non-technical audiences.

• Balance strategic improvements to the platform with urgent operational and customer demands.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, or a related field, or equivalent experience.

• Over 5 years of experience in data engineering and data platform management.

• More than 2 years of experience in technical leadership and mentoring engineers.

• Extensive hands-on experience in designing, building, and managing production data platforms and pipelines.

• Strong expertise in data architecture, ingestion, orchestration, transformation, modeling, warehousing, and performance optimization.

• Advanced SQL capabilities along with strong proficiency in Python and PySpark.

• Experience with dbt, Apache Airflow, AWS Glue, or similar tools.

• Proven experience in designing dimensional models, star schemas, and curated analytical layers.

• Demonstrated accountability for data quality and reliability, including testing, monitoring, lineage, reconciliation, and operational support.

• Experience in creating dashboards, reports, semantic layers, and self-service datasets using Sigma, Looker, or similar platforms.

• Solid backend engineering fundamentals, including knowledge of APIs, distributed systems, and event-driven architectures.

• Experience in directly engaging with customers, executives, and cross-functional stakeholders.

• Exceptional written and verbal communication skills.

• Strong sense of ownership, urgency, judgment, resourcefulness, and follow-up.

• A hands-on leadership approach with a willingness to tackle challenging problems personally.

• Capability to lead effectively across different time zones.

🏝️ Benefits

• Comprehensive health, dental, and vision insurance.

• Flexible work hours and remote work options.

• Generous vacation and paid time off policies.

• Opportunities for professional development and career advancement.

• Collaborative and inclusive company culture.