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EXL

Data Engineer

Posted 3 Days Ago
Remote
Hiring Remotely in United States
Senior level
Remote
Hiring Remotely in United States
Senior level
Lead architecture and delivery of a cloud-native, petabyte-scale data platform: define technical roadmap, mentor engineers, build ETL/ELT pipelines, enable real-time streaming, implement Iceberg table format, optimize Snowflake/Redshift/Athena compute, and integrate observability with Splunk.
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We are seeking an experienced and visionary Senior Full-Stack Data Engineer to lead the architecture, development, and optimization of a next-generation data platform. This is a critical role for an individual with over 10 years of deep data engineering expertise, capable of driving technical direction, mentoring team members, and delivering high-impact solutions in a fast-paced project environment..

Responsibilities
  • Platform Strategy & Leadership 
    • Technical Direction: Define and champion the architectural roadmap and best practices for our end-to-end data pipelines, ensuring scalability, reliability, and security across the platform.
    • Team Mentorship & Project Velocity: Act as a primary technical mentor, guiding a team of engineers, conducting code reviews, and aggressively driving the project timeline to ensure rapid delivery of data products.
    • Stakeholder Collaboration: Partner with Data Scientists, Analysts, and business stakeholders to translate complex requirements into robust, production-ready data solutions.
    • Collaboration with Data Scientists and ML Engineers:  Data Accessibility, Support for Model Development, Data Quality Assurance
  • Data Pipeline Development & Management
    • Ingestion & Transformation: Design, build, and optimize high-volume data ingestion and transformation jobs using tools like dbt Core, AWS Glue, ensuring data quality and integrity.
    • Workflow Orchestration: Develop and maintain sophisticated data pipelines using orchestrators such as Dagster, focusing on modularity and reusability.
    • Streaming & Real-time Integration: Implement and manage real-time data flows utilizing Confluent platforms or native AWS streaming services (e.g., Kinesis) for immediate data availability.
    • Data Security and Privacy: Data Anonymization, Compliance with Regulations
    • Be well versed with DataOps and DevOps fundamentals
  • Assist and drive the Data Ecosystem Management & Monitoring
    • Open Table Formats & Management: Implement and maintain the Iceberg open table format, utilizing tools for efficient schema evolution and data management.
    • Compute Engine Optimization: Optimize query performance and cost efficiency across our primary compute engines: Snowflake, Amazon Redshift, and AWS Athena.
    • Observability & Monitoring: Integrate comprehensive monitoring and observability into all pipelines using Splunk to ensure high availability, rapidly identify bottlenecks, and troubleshoot production issues
Qualifications
  • 10+ Years of hands-on, progressive experience in Data Engineering, Data Architecture, or a closely related Full-Stack Data role
  • Deep conceptual understanding of core data engineering principles, ETL/ELT patterns, and metadata management 
  • Proven track record of building and managing petabyte-scale data infrastructure in a cloud-native environment 
  • Insurance industry experience preferred but not mandatory
  • Tools:
    • Cloud Environment: AWS (S3, IAM, VPC, etc.)
    • Experience with Talend, dbt Core, Iceberg, AWS Glue Catalog, Snowflake, Redshift, Athena, Splunk, AWS streaming services, Git

Strong SQL, Pyspark and Python

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