Senior Data Engineer – Data Platform

About This Opportunity

We are representing a confidential financial services organization seeking a Senior Data Engineer - Data Platform to join their growing data infrastructure team. This role will be responsible for building and operating the foundational data infrastructure that powers analytics, reporting, and operational workflows across the organization. You'll design, develop, and maintain scalable batch and streaming pipelines, curated data models, and platform services that enable internal teams to access reliable, well-governed data.

This is a remote position based in the United States.

Responsibilities

• Design, build, and operate end-to-end data pipelines (batch and near-real-time) that ingest, transform, and deliver data from diverse sources into the enterprise data platform
• Develop and maintain curated data models, marts, and shared datasets in Snowflake and PostgreSQL that meet performance, quality, and access-control requirements for multiple internal customers
• Implement data quality frameworks including automated validation, schema enforcement, reconciliation checks, duplicate detection, and exception reporting with clear audit trails
• Partner with domain teams to understand data needs, define contracts and SLAs, and deliver platform capabilities that reduce bespoke engineering and manual effort
• Build parameterized, reusable pipeline components and templates that standardize ingestion patterns, transformations, and deployment across the platform
• Establish and maintain data lineage, metadata, and documentation so stakeholders can trace data from source to consumption with confidence
• Collaborate with IT and security to implement role-based access controls, data masking, encryption, and compliance requirements across platform resources
• Own pipeline orchestration, scheduling, dependency management, and alerting using workflow tools to ensure reliable, recoverable execution
• Improve platform observability through logging, metrics, SLA monitoring, and incident response practices that minimize downtime and data freshness gaps
• Support CI/CD and infrastructure-as-code practices for data platform assets, including version control, automated testing, and safe promotion across environments
• Evaluate and integrate new platform technologies and patterns where they improve scalability, cost efficiency, or time-to-value
• Mentor junior engineers and contribute to platform standards, code review practices, and technical design documentation

What We're Looking For

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field
• 5+ years of experience in data engineering or platform engineering, preferably in financial services or a regulated industry
• Strong SQL and Python skills, with a track record of building production-quality data pipelines, transformations, and validation frameworks
• Proficient at using AI-assisted development tools to design, build, and iterate on data pipelines while maintaining code quality, security, and governance standards
• Hands-on experience with Snowflake and PostgreSQL, including performance tuning, cost optimization, and secure multi-tenant data access patterns
• Experience with pipeline orchestration and workflow management 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 (preferred)
• Experience with cloud data services (AWS, Azure, or GCP) and infrastructure-as-code such as Terraform is strongly preferred
• Exposure to streaming or change-data-capture (CDC) patterns and event-driven architectures is a plus
• Understanding of financial data domains is helpful but not required; curiosity and ability to partner with domain experts is essential
• Strong communication and collaboration skills; ability to translate ambiguous requirements into well-scoped technical designs and clear status reporting
• Familiarity with containerization (Docker/Kubernetes) and API/integration patterns for data services is a plus

How We Work With You

When you apply through Get A Job.ai, our recruiting team will review your background and qualifications. If there's a strong match, we'll schedule a screening conversation to discuss your experience, technical skills, and career goals. Once aligned, we'll submit your profile to our client for consideration. Throughout the interview process, we'll provide guidance and feedback to help you succeed.

Please apply only through Get A Job.ai. Do not attempt to contact the client directly, as all applications must be coordinated through our talent team to be considered.

Pay

Compensation details will be discussed during the screening process and are dependent on experience and qualifications.

Equal Employment Opportunity: Get A Job.ai is committed to providing equal employment opportunities to all applicants regardless of race, color, religion, sex, national origin, age, disability, or any other protected characteristic. We celebrate diversity and are dedicated to creating an inclusive environment for all candidates.