Senior Data Engineer - Data Platform
SunStrong Management, LLC4 months ago
Remote, United StatesSenior
Responsibilities
- Design, build, and operate batch and near-real-time data pipelines for diverse internal and third-party sources.
- Develop and maintain curated data models, marts, and shared datasets in Snowflake and PostgreSQL.
- Implement automated data quality controls including validation, schema enforcement, reconciliation, duplicate detection, exception reporting, and audit trails.
- Partner with Asset Management, Finance, Operations, IT, security, and other stakeholders to define data contracts, SLAs, and platform capabilities.
- Build reusable, parameterized pipeline components, templates, ingestion patterns, transformations, and deployment standards.
- Maintain data lineage, metadata, documentation, governance, role-based access controls, masking, encryption, and compliance requirements.
- Own pipeline orchestration, scheduling, dependency management, alerting, observability, incident response, and data freshness monitoring.
- Support version control, automated testing, CI/CD, infrastructure-as-code, and safe promotion across environments.
- Evaluate streaming, CDC, data mesh, and other platform patterns for scalability, cost efficiency, and delivery speed.
- Mentor junior engineers and contribute to code reviews, platform standards, and technical design documentation.
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field.
- At least 5 years of experience in data engineering or platform engineering.
- Strong SQL and Python skills with experience building production-quality pipelines, transformations, and validation frameworks.
- Proficiency with AI-assisted development tools while maintaining code quality, security, and governance standards.
- Hands-on experience with Snowflake and PostgreSQL, including performance tuning, cost optimization, and secure multi-tenant access patterns.
- Experience with workflow orchestration tools such as Apache Airflow, Dagster, or equivalent.
- Proficiency with Git, code review, and CI/CD practices for data platform development.
- Experience designing dimensional or domain-oriented data models and delivering curated datasets for analytics and operational use cases.
- Familiarity with data quality, lineage, and governance tooling and practices is preferred.
- Experience with AWS, Azure, or GCP and infrastructure-as-code such as Terraform is strongly preferred.
- Exposure to streaming, change-data-capture patterns, and event-driven architectures is a plus.
- Understanding of financial data domains such as portfolio, investor reporting, accounting, or related regulated-industry experience is helpful but not required.
- Strong communication and collaboration skills, including translating ambiguous requirements into technical designs and clear status reporting.
- Familiarity with Docker, Kubernetes, and API or integration patterns for data services is a plus.
Tech Stack
Categories
Data Engineering