Data Engineer – Modern Data Platform
Role Overview
We are looking for an experienced, hands-on Data Engineer with strong expertise in Fivetran, dbt, Snowflake, and modern cloud data engineering practices. The candidate should also have experience with Python, and familiarity with AI-assisted development tools such as Claude, Cursor, or VS Code-based AI assistants.
The role will focus on building scalable ingestion and transformation pipelines, implementing data quality and orchestration patterns, and supporting enterprise data products consumed by analytics and business teams.
Core Responsibilities
- Design, build, and support end-to-end data pipelines using Fivetran, dbt, and Snowflake.
- Configure and manage Fivetran connectors across SaaS applications, databases, APIs, and file-based sources.
- Develop and maintain dbt models, including staging, intermediate, mart, and publish layers.
- Implement dbt testing, source freshness, incremental processing, documentation, and reusable macros.
- Develop optimized Snowflake SQL and scalable analytical data models.
- Support Snowflake objects, security/RBAC, stages, data sharing, and data-loading patterns.
- Implement data quality, reconciliation, monitoring, and operational alerting.
- Troubleshoot production pipelines and perform root-cause analysis across ingestion and transformation layers.
- Participate in Git-based development, CI/CD, code reviews, and DEV/QA/PROD deployments.
- Collaborate with application, infrastructure, security, analytics, and business teams to onboard new data sources.
Required Technical Skills
Strong hands-on experience with:
- Snowflake – Advanced SQL, data modeling, performance optimization, RBAC, stages, and data integration patterns.
- dbt / dbt Cloud – Models, tests, macros, incremental models, sources, documentation, jobs, and deployment patterns.
- Fivetran – Connector configuration, schema management, sync troubleshooting, monitoring, and ingestion architecture.
- SQL – Complex joins, CTEs, window functions, reconciliation, and query optimization.
- Git / CI/CD – Branching, pull requests, code reviews, and automated deployment workflows.
Python
Working knowledge of Python is preferred, particularly for data processing, automation, API integrations, file processing, data validation, and operational scripting.
Advanced Python development is not required, but candidates should be comfortable reading, troubleshooting, and developing Python-based data engineering utilities.
AI-Assisted Development
Familiarity with Claude and AI-assisted development workflows is preferred; deep AI/LLM development experience is not required.
Candidates should be comfortable using tools such as:
- Claude
- Cursor
- VS Code with AI-assisted development capabilities
Typical use cases may include:
- Developing and troubleshooting SQL, dbt, and Python code.
- Code review, refactoring, and debugging.
- Generating unit/data-quality tests.
- Understanding existing codebases and data pipelines.
- Creating technical documentation.
- Accelerating day-to-day data engineering development while following enterprise security and development standards.
Good to Have
- Apache Airflow / AWS MWAA for orchestration.
- AWS services such as S3, IAM, Lambda, Secrets Manager, and FSx.
- Salesforce, Marketo, and other SaaS integrations.
- REST API and SFTP/file-based ingestion.
- Snowflake Secure Data Sharing.
- Snowpark / Snowpark Container Services (SPCS).
- Databricks.
- Terraform / Infrastructure as Code.
- Data quality and observability frameworks.
- Experience modernizing or migrating legacy ETL/integration platforms.
Preferred Experience
- 5+ years of Data Engineering or related experience.
- 2+ years of hands-on experience with Snowflake and dbt.
- Production experience implementing and supporting Fivetran pipelines.
- Experience operating within enterprise DEV → QA → PROD SDLC and change-management processes.
- Experience designing reusable ingestion and transformation patterns.
- Strong production troubleshooting and root-cause analysis skills.
Candidate Profile
We are specifically looking for a hands-on Data Engineer, rather than primarily a BI/reporting developer.
The ideal candidate should be comfortable owning and troubleshooting the complete data lifecycle:
Source → Fivetran → Snowflake → dbt
The candidate should also be comfortable using Claude through modern development environments such as Cursor or VS Code to improve engineering productivity, troubleshooting, documentation, and code quality.
ResponsibilitiesManage data modelling projects. Ensure adherence to policies. Provide strategic guidance. Lead a team. QualificationsGraduate in Computer Science, Data Science, or a related field. 4-6 years of experience in data modelling or data analysis.
Skills Required
- Strong hands-on experience with Snowflake, including advanced SQL, data modeling, performance optimization, RBAC, stages, and data integration
- Strong hands-on experience with dbt or dbt Cloud, including models, tests, macros, incremental models, sources, documentation, jobs, and deployments
- Production experience implementing and supporting Fivetran pipelines, connectors, schema management, troubleshooting, and monitoring
- Strong SQL skills, including complex joins, CTEs, window functions, reconciliation, and query optimization
- Experience with Git, branching, pull requests, code reviews, and CI/CD workflows
- Working knowledge of Python for data processing, automation, API integrations, file processing, validation, and operational scripting
- Familiarity with Claude or AI-assisted development tools such as Cursor or Visual Studio Code AI assistants
- Five or more years of data engineering or related experience
- Two or more years of hands-on Snowflake and dbt experience
- Experience operating within enterprise DEV, QA, and PROD SDLC and change-management processes
- Graduate degree in Computer Science, Data Science, or a related field
- Apache Airflow or AWS MWAA orchestration experience
- Experience with AWS services, SaaS integrations, REST APIs, SFTP, Snowflake Secure Data Sharing, Snowpark, Databricks, Terraform, or data observability frameworks
EXL Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about EXL and has not been reviewed or approved by EXL.
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Healthcare Strength — Medical plan options include HSA, HRA, and PPO choices, with additional health-related programs such as disability coverage and an employee assistance program. Feedback suggests these options provide meaningful flexibility and coverage breadth for many roles.
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Leave & Time Off Breadth — Up to 20 days of paid time off, plus federal holidays and paid sick and safe time, are highlighted. Feedback suggests this leave structure is a notable benefit alongside core compensation.
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Retirement Support — A traditional and Roth 401(k) with up to a 3% company match and full vesting after one year is described. Feedback suggests this match and vesting timeline help bolster long-term savings.
EXL Insights
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.
