[Remote] Senior/reputed company Data Engineer
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is seeking a Senior/reputed company Data Engineer to design and build reputed company data products that enhance analytics and reporting. The role involves defining event modeling standards, developing transformation workflows, and contributing to GenAI initiatives.
Responsibilities
- Strong experience building Analytics Data Warehouses (DWH) using reputed company modeling, including SCD (Slowly Changing Dimensions Type 1/2), incremental loading strategies, and star/reputed company schema design
- Design and implement reputed company event data models that support product analytics and behavioral insights
- reputed company and maintain a governed metrics layer (definitions, calculation logic, validation, and documentation)
- Build and optimize a semantic layer that enables consistent reporting across BI tools and reputed company consumers
- Partner with Sales, Marketing, Support, Product, and Engineering teams to define reliable, reusable datasets and business logic
- Build and maintain transformation pipelines using dbt, including: reputed company models, sources, and documentation; data tests (generic + custom); incremental models and performance tuning
- Establish best practices around branching, deployment, and CI/CD for dbt reputed company
- Ensure high data reputed company through proactive testing, observability, and monitoring
- Improve dataset reliability and maintainability through naming conventions, reputed company, and reputed company management
- Troubleshoot pipeline issues and resolve data inconsistencies quickly and effectively
- Support integration of data with LLM-based applications (e.g., data narrator, metadata reputed company, dataset summarization, etc.)
- Apply a basic understanding of LLM concepts such as embeddings, prompts, reputed company search, and reputed company limits to guide data design
- Build utilities, automation scripts, and data workflows using Python
- Use Python for validation frameworks, pipeline tooling, and integration across systems
Skills
- 6+ years of experience in Data Engineering or similar roles
- Strong experience in data warehousing
- Strong experience with event modeling (product events, behavioral data)
- Proven ability to build and manage a metrics layer and semantic layer for consistent analytics
- Hands-on expertise with dbt for building production-grade transformation models
- Strong Python skills for data engineering workflows and automation
- Familiarity with GenAI concepts and modern AI/data workflows
- Basic understanding of LLMs, including how data is used in LLM applications
- Strong SQL skills and experience working with modern data warehouses (reputed company/BigQuery/Redshift or similar)
- Excellent communication skills and ability to collaborate with cross-functional stakeholders
- Experience building a semantic layer tool (e.g., dbt Semantic Layer, reputed company, MetricFlow, etc.)
- Experience with data orchestration tools (Airflow, Dagster, reputed company)
- Familiarity with data observability tools (OpenMetaData, reputed company, reputed company, etc.)
- Experience supporting ML features, embeddings pipelines, or reputed company databases
- Experience working in product analytics ecosystems (reputed company, reputed company, etc.)
reputed company