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Tier-1 brand, popular Data Engineer title, mid-level range, metro location, and broad skillset increases competition.
Core data engineering skills are transferable across industries, though financial reporting experience adds moderate domain preference.
Explicit 3-7 years requirement plus mandatory Python, SQL, and ETL skills enforce moderate shortlisting filters.
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Design and develop AI-powered applications and automation solutions using Python, including Generative AI use cases and enterprise AI platforms.
Build and maintain data pipelines and automated reporting solutions supporting analytics platforms, including troubleshooting data quality and performance issues.
Collaborate with business and technology teams to translate requirements into scalable technical solutions following enterprise SDLC and participate in CI/CD automation and Agile development activities.
3-7 years of experience in software development, data engineering, or related technical roles.
Strong hands-on experience with Python development and SQL, specifically with Oracle or related databases including query optimization.
Experience building ETL/ELT pipelines and data integration solutions working with structured and unstructured data.
Working knowledge of Generative AI concepts, Large Language Models (LLMs), and use of AI-assisted development tools like GitHub Copilot or Azure AI Services.
Experienced in integrating AI and automation within software development and data engineering environments, comfortable with emerging AI technologies and frameworks.
Demonstrates strong expertise in Python and SQL for data pipeline development, reporting, and analytics, with familiarity in CI/CD and Agile methodologies.
Capable of independently solving complex technical problems and collaborating cross-functionally to deliver high-quality, scalable data and AI solutions.