Data Engineer
$135k - $165kCollabera
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Days Left: 29 days, 4 hours left Apply Title: Senior Data Engineer - AI & Platform Location: US - Remote (EST/CST) Employment: Full-Time opportunity
Salary Range: $135k/ann.-$165k/ann. Key Responsibilities:
- Design, build, and maintain scalable, self-healing data pipelines using Databricks, Python, PySpark, and SQL.
- Develop data pipelines across Bronze, Silver, and Gold/Certified Gold layers, ensuring data quality and reliability.
- Ingest, transform, and serve data from dozens of source systems, including enterprise applications, financial systems, IoT, web/mobile analytics, and third-party platforms.
- Build error recovery and quarantine workflows to isolate failed records while allowing valid data to continue through the pipeline.
- Implement schema validation, data quality checks, anomaly detection, automated testing, regression testing, and data observability.
- Develop and maintain data models with proper data grain, keys, referential integrity, lineage, and governance.
- Build infrastructure that supports AI/ML workloads, including feature stores, embedding pipelines, vector search, and real-time serving layers.
- Build and maintain MCP server integrations that expose enterprise data to LLM-powered tools and AI agents.
- Develop integrations that allow AI applications to connect to, query, and retrieve data through MCP servers.
- Design and implement RAG (Retrieval-Augmented Generation) architectures and integrate LLM-powered solutions with enterprise data.
- Work with vector databases such as Pinecone, Weaviate, or similar technologies.
- Support AI model training, evaluation, deployment, monitoring, and productionization in partnership with Data Science and Product teams.
- Evaluate AI-powered data engineering and data quality tools, including solutions for automated schema detection, cataloging, completeness checks, and data validation.
- Use AI-assisted testing and evaluation approaches to validate data and AI outputs against business requirements.
- Develop APIs and data interfaces that enable AI products and internal applications to query and interact with data in real time.
- Implement data governance practices covering access controls, PII handling, data classification, compliance, and appropriate AI data usage.
- Build monitoring, alerting, SLA tracking, and data freshness capabilities into data platforms.
- Document data models, pipeline architectures, AI integrations, and reusable engineering patterns.
- 5+ years of experience in Data Engineering, working with data from multiple enterprise source systems.
- Strong hands-on experience with Databricks.
- Strong Python and PySpark development experience.
- Strong SQL skills.
- 2-3+ years of hands-on experience with MCP Servers / Model Context Protocol.
- Hands-on experience building and implementing RAG models/architectures.
- Experience connecting to, querying, and integrating data through MCP servers.
- Strong experience building self-healing or fault-tolerant data pipelines and error recovery workflows.
- Experience with schema validation and data quality frameworks.
- Strong understanding of Bronze/Silver/Gold data architecture.
- Experience with LLM integration patterns, AI agents, tool-use frameworks, and AI-enabled data solutions.
- Experience with vector databases such as Pinecone, Weaviate, or equivalent.
- Experience building data pipelines and infrastructure suitable for AI/ML workloads.
- Understanding of data governance, lineage, monitoring, observability, and data quality.
- MCP
- RAG
- Pyspark
- Recruiter
- Phone
- Christin Mathew
- View email address on click.appcast.io
Vacancy posted 4 days ago
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