Strategic Data & Analytics Engineer
New
J
JobgetherData & Analytics
United States and CanadaFull-TimeSenior
Salary120,000 - 140,000 USD per year
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Job Details
- Experience
- 5+ years of hands-on experience in data engineering, analytics engineering, or data architecture; 2+ years of experience in a client-facing, consultative, or strategic leadership capacity
- Required Skills
- PythonSQLSnowflakeData engineeringdbtDatabricksPySpark
Requirements
- 5+ years of hands-on experience in data engineering, analytics engineering, or data architecture.
- 2+ years of experience in a client-facing, consultative, or strategic leadership capacity.
- Hands-on expertise with modern cloud data platforms (Databricks, Snowflake, or equivalent).
- Advanced proficiency in SQL, Python/PySpark, and dbt.
- Strong understanding of dimensional models, Medallion architectures, identity resolution, and graph-like structures.
- Experience with MarTech, Customer Data Platforms (CDPs), reverse ETL (e.g., Hightouch, Census), and CRM ecosystems.
- Practical understanding of agentic AI, LLM context retrieval, and autonomous workflows.
- Knowledge of data governance, metadata management, business glossaries, and data cataloging.
- Excellent communication skills for technical and non-technical audiences.
- Ability to work autonomously in a remote and distributed environment.
- Professional certifications in Databricks or Snowflake are preferred.
Responsibilities
- Partner with business leaders to translate strategic objectives into scalable data engineering and architecture solutions.
- Design and maintain enterprise marketing data models, semantic layers, ontologies, and warehouse-native architectures.
- Architect semantic context layers designed to support LLM-powered applications, autonomous AI agents, and context retrieval.
- Develop identity resolution models and graph-oriented structures to connect customer data across CRM and digital touchpoints.
- Lead cross-system integrations connecting cloud warehouses, CDPs, MarTech platforms, and real-time telemetry.
- Implement data governance, metadata management, and data quality practices to support secure self-service analytics.
- Communicate architectural decisions and technical trade-offs to executives and cross-functional teams.
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