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Popular data-engineer title, metro location, broad skillset and hybrid role increase applicant competition.
Core data-engineering skills are transferable, but AI/LLM and specialized web-scraping raise domain specificity.
Numerous mandatory technical skills (SQL, Python, BigQuery, web-scraping, LangChain) increase filtering stringency.
Develop, test, and maintain data tools, automation, and scalable ETL/ELT pipelines using SQL, Python, and web-scraping technologies to support Research and Managed Services.
Identify, evaluate, document, and recommend data sources feeding AI solutions and workflows; implement and monitor AI-enabled workflows leveraging LangChain or equivalent frameworks.
Perform operational tasks including database administration, data maintenance, incident resolution, and ensure data integrity and compliance with governance standards.
Strong skills in SQL and Python, including coding and maintaining data workflows.
Experience with web data collection tools like Playwright, Selenium, and managing data ingestion from various formats (delimited files, XML, JSON, PDF).
Work Experience Required: Not explicitly mentioned in the JD.
Hands-on experience implementing AI solutions using LangChain or equivalent, and familiarity with AI-related technologies such as large language models and prompt engineering.
Comfortable working in an agile environment with cross-functional teams across Data & Analytics, Technology, Product, and Research Services.
Experienced in operational data management and database administration, capable of end-to-end ownership of data pipelines and supporting workflows.
Able to evaluate and apply emerging AI and data technologies effectively to improve automation, data quality, and workflow scalability.