What are the responsibilities and job description for the Forward Deployed Engineer position at EXL?
What Makes This Role Different
- Work alongside client teams in high-impact environments, moving from problem discovery to production deployment.
- Combine business and functional understanding with deep engineering execution rather than operating only as an advisory architect.
- Own measurable outcomes across solution design, application development, data engineering, adoption, and production readiness.
- Build reusable accelerators and patterns while adapting solutions to client-specific workflows and constraints.
- Partner with business stakeholders, product owners, analysts, and technology leaders to understand objectives, pain points, KPIs, users, and operating constraints.
- Lead discovery sessions, functional workshops, architecture reviews, technical demonstrations, prototypes, and proof-of-concepts.
- Translate ambiguous business problems into prioritized use cases, user stories, technical designs, delivery plans, and measurable success criteria.
- Act as a trusted technical advisor and maintain close engagement through implementation, rollout, adoption, and stabilization.
- Develop a strong understanding of client business processes, workflows, policies, data definitions, controls, and decision-making needs.
- Perform process analysis and identify opportunities for application modernization, workflow automation, data enablement, and AI-assisted decision support.
- Define functional requirements, acceptance criteria, business rules, source-to-target mappings, and operational scenarios in partnership with business users.
- Ensure solutions are usable, explainable, aligned with business outcomes, and supported by clear documentation and training materials.
- P&C Insurance domain experience is good to have
- Design, develop, test, deploy, and support enterprise applications, data applications, APIs, microservices, and workflow solutions on Azure.
- Build backend services using Python etc..to develop user interfaces using React or Angular where required.
- Integrate applications with Snowflake, Databricks, Azure services, REST APIs, enterprise platforms, and third-party systems.
- Apply secure software development practices, modular design, automated testing, observability, error handling, and performance engineering.
- Own the full software development lifecycle, including requirements, design, coding, reviews, release, production support, and continuous improvement.
- Design and build scalable batch, streaming, and event-driven pipelines using ADF, Databricks, Snowflake, and related Azure services.
- Implement lakehouse, data lake, and cloud data warehouse patterns, including bronze, silver, and gold data layers.
- Develop ETL/ELT workflows, reusable ingestion frameworks, business-ready datasets, dimensional models, and data quality controls.
- Optimize Spark, PySpark, SQL, Snowflake workloads for performance, reliability, scalability, and cost.
- Implement metadata management, lineage, access controls, monitoring, reconciliation, and operational support processes.
- Design cloud-native architectures that meet security, scalability, resilience, integration, and maintainability requirements.
- Implement CI/CD pipelines, infrastructure as code, automated testing, release controls, and environment promotion using Azure DevOps, GitHub, and Terraform.
- Create solution documentation, data-flow diagrams, support playbooks, and operational runbooks.
- Drive code reviews, engineering standards, root-cause analysis, production stabilization, cross-training, and knowledge transfer.