Data Engineer

EXL

. Define and champion the architectural roadmap and best practices for end-to-end data pipelines, ensuring scalability, reliability, and security .

Posted 10/3/2026full-timeRemote • United StatesSeniorLead💰 $85,000 - $140,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and optimizing scalable data pipelines and architectures, with a strong focus on data security, quality assurance, and compliance. Proficient in leveraging cloud-native technologies and tools to build and manage high-volume data infrastructures.

Highest-signal resume keywords

Data EngineeringData ArchitectureAWS GlueSQLPySpark

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentETL/ELT PatternsMetadata ManagementData AnonymizationQuery Optimization

Soft Skills

MentoringCollaborationProject Management

Tools & Technologies

Dbt CoreSnowflakeAmazon RedshiftAWS AthenaSplunk

Industry Keywords

Cloud-Native EnvironmentDataOpsDevOpsInsurance Industry Experience

Tech Stack

Tools & technologies

Amazon RedshiftAWSCloudETLPySparkPythonSplunkSQL

About the role

Key responsibilities & impact

Define and champion the architectural roadmap and best practices for end-to-end data pipelines, ensuring scalability, reliability, and security
Mentor engineers, conduct code reviews, and drive project timelines for rapid delivery of data products
Partner with Data Scientists, Analysts, and business stakeholders to translate requirements into production-ready data solutions
Collaborate with Data Scientists and ML Engineers on data accessibility, model development support, and data quality assurance
Design, build, and optimize high-volume data ingestion and transformation jobs using dbt Core and AWS Glue
Develop and maintain modular, reusable data pipelines using orchestrators such as Dagster
Implement and manage real-time data flows using Confluent platforms or native AWS streaming services such as Kinesis
Implement data anonymization and comply with data security and privacy regulations
Implement and maintain the Iceberg open table format for schema evolution and data management
Optimize query performance and cost efficiency across Snowflake, Amazon Redshift, and AWS Athena
Integrate monitoring and observability into pipelines using Splunk to identify bottlenecks and troubleshoot production issues

Requirements

What you’ll need

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
Experience with AWS, including S3, IAM, and VPC
Experience with Talend, dbt Core, Iceberg, AWS Glue Catalog, Snowflake, Redshift, Athena, Splunk, AWS streaming services, and Git
Strong SQL, PySpark, and Python
Familiarity with DataOps and DevOps fundamentals

Benefits

Comp & perks

Annual bonus
Benefits information provided at https://www.exlservice.com/us-careers-and-benefits
Remote work / work from home