Work Location: United States
Work Mode : Remote
Pay Range :$85K-$140K /Yr Base + Annual Bonus
The posted range is the hiring range for this role — a subset of the broader
range available to employees over time — and reflects base salary across our
national hiring scale. Final offers are based on several factors, including the
candidate's skills and experience, internal pay equity, work location, market
conditions for the role, and the specific scope and responsibilities of the
position. The top of the range is reserved for candidates who notably exceed the
requirements; the lower end applies to those with less experience or fewer
preferred qualifications. For positions based in higher-cost zones (e.g.,
California, New York, New Jersey), actual compensation may exceed the posted
range; your recruiter will share specifics during the process
For more information on benefits and what we offer please visit us
at https://www.exlservice.com/us-careers-and-benefits
[https://www.exlservice.com/us-careers-and-benefits]
Job Overview:
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