Sr. Data Engineer
Remote (United States)
Compensation
Estimated hourly pay:$72.12 - $91.35 per hour
Employment Type
Full-Time
About the Role
This opportunity is for a Senior Data Engineer to help design, build, and scale high-throughput data infrastructure for a large production platform. The role focuses on streaming pipelines, large-scale data ingestion, data modeling, data quality, and AI-assisted engineering workflows.
This position is suited for a senior engineer who is highly comfortable using AI tools as part of daily development work and who can connect technical architecture decisions to product outcomes, customer value, and long-term business needs.
What You’ll Do
- Build, scale, and operate high-throughput streaming pipelines that process large volumes of data from hundreds of integrations.
- Design and maintain pipelines using technologies such as Airflow, Spark Streaming, Kafka, and Iceberg.
- Ensure pipeline reliability, performance, and data correctness across large-scale production systems.
- Develop and maintain high-quality production datasets that power core product experiences.
- Focus on data modeling, transformation logic, freshness, accuracy, and cost efficiency.
- Implement and improve data quality checks, monitoring, alerting, and observability practices.
- Detect data issues early and reduce downstream impact through stronger reliability controls.
- Contribute to AI-driven tooling that helps triage, debug, and resolve data quality issues.
- Use AI to improve data operations, increase team efficiency, and reduce manual intervention.
- Shape platform architecture and contribute to AI-powered product delivery.
- Help raise the engineering standard for a small, AI-augmented technical team.
Qualifications
- 6+ years of professional experience in data engineering or software engineering.
- Strong experience with distributed data processing and streaming systems, including Spark, PySpark, and Kafka.
- Proficiency in Python, with Pydantic experience preferred.
- Familiarity with Node.js or TypeScript is a plus.
- Experience building and maintaining data pipelines on AWS using tools such as Airflow, Spark Streaming, and Iceberg.
- Solid understanding of data modeling and large-scale dataset management.
- Familiarity with event-driven systems and ingestion patterns using Kafka, SQS, or similar technologies.
- Experience implementing data quality checks, monitoring workflows, and debugging data issues.
- Interest in applying AI, machine learning, or automation to improve data workflows.
- Proven track record leading high-impact initiatives from concept through production in a SaaS environment.
- Expert-level understanding of software design principles.
- Experience with multi-tenant platform architectures.
- Ability to use AI tools as a core part of the engineering workflow.
- Strong systems thinking and ability to connect technical decisions to customer outcomes and business value.
- Clear communication skills and the ability to explain complex tradeoffs to product, design, and executive stakeholders.
- Ability to work effectively in fast-changing environments with ambiguity, speed, and high ownership.
Tech Stack
- Backend: Python, PySpark, Pydantic, Node.js, TypeScript
- Data: Iceberg, PostgreSQL
- Infrastructure: AWS, Kubernetes, Airflow, Spark Streaming
- Messaging: Kafka, SQS
If you notice a problem with this job, email us at
contact@7seventy.net.
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