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
- 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
Skills Required
- 10+ years hands-on experience in Data Engineering or Full-Stack Data roles
- Proven experience building and managing petabyte-scale cloud-native data infrastructure
- Deep understanding of ETL/ELT patterns, metadata management, and core data engineering principles
- Experience with AWS cloud services (S3, IAM, VPC, etc.)
- Experience with dbt Core
- Experience with AWS Glue and AWS Glue Catalog
- Experience implementing/open table formats such as Iceberg
- Experience with workflow orchestration using Dagster
- Experience with streaming platforms (Confluent) or AWS streaming services (Kinesis)
- Experience optimizing compute on Snowflake, Amazon Redshift, and AWS Athena
- Experience with observability/monitoring using Splunk
- Experience with Talend
- Proficiency in SQL
- Proficiency in PySpark
- Proficiency in Python
- Familiarity with Git
- Knowledge of DataOps and DevOps fundamentals
- Ability to mentor engineers, conduct code reviews, and drive project timelines
- Insurance industry experience
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.
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