Job DescriptionData Engineer - Modern Data PlatformRole OverviewWe 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 SkillsStrong 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.
PythonWorking 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 DevelopmentFamiliarity 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 12 QA 12 PROD SDLC and change-management processes.
- Experience designing reusable ingestion and transformation patterns.
- Strong production troubleshooting and root-cause analysis skills.
Candidate ProfileWe 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 12 Fivetran 12 Snowflake 12 dbtThe 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.
