{bc}
oracle

Data Engineer II

American Express
Gurugram, IND
Full-time
Mid · 5+ years experience
Hybrid
Discovered 1 weeks ago
airflowgcpgithadoophivekafka

Full Job Posting

Minimum Qualifications

  • Bachelor's or master's degree in computer science, Engineering or a related technical discipline, or equivalent work experience.
  • 5+ years of hands-on experience in software development or data engineering, preferably with large-scale Big Data and cloud-based solutions.
  • Strong hands-on expertise in SQL, Python, GCP Big Query and Apache Airflow, including developing and optimizing complex data pipelines.
  • Experience with Spark, Scala, Hadoop/Hive or equivalent distributed data-processing technologies.
  • Strong data analysis and problem-solving skills, including data profiling, complex SQL, source-to-target validation, data reconciliation and root cause analysis.
  • Experience in ETL/ELT, data modeling, data transformation, workflow orchestration and performance optimization.
  • Practical hands-on experience with Generative AI tools such as GitHub Copilot, ChatGPT Enterprise or equivalent AI coding assistants for development, debugging, testing or automation.
  • Working knowledge of LLMs, prompt engineering and responsible AI practices, particularly secure handling of enterprise and sensitive data.
  • Experience with Git/GitHub, CI/CD pipelines, automated testing and software development best practices.
  • Understanding of data-quality controls, data governance, privacy and production support.
  • Strong communication skills, ability to collaborate across teams and independently resolve complex technical problems.

Preferred Qualifications

  • Experience with GCP Bigtable, Pub/Sub, Dataflow, Kafka or real-time data-processing frameworks.
  • Exposure to Adobe Experience Platform, Adobe Journey Optimizer or Customer Journey Analytics.
  • Experience building or contributing to AI-enabled data engineering solutions, such as automated RCA, data-quality monitoring, intelligent data discovery, lineage or test-data generation.
  • Familiarity with LLM APIs, Retrieval-Augmented Generation (RAG), agentic AI frameworks or AI workflow automation.
  • Experience developing enterprise data products supporting Marketing, Banking, Lending or customer engagement.
  • GCP Professional Data Engineer or equivalent cloud certification.

Responsibilities

  • We are looking for a skilled and motivated Engineer II with strong hands-on experience in Data Engineering, Big Data technologies, GCP, Python, SQL and AI-assisted software development.
  • Data Engineering & Development: Design, develop and maintain scalable data pipelines using GCP BigQuery, Python, SQL, Spark and Apache Airflow for large-scale data ingestion, transformation and processing.
  • Data Analysis & Quality: Perform data discovery, profiling, complex SQL analysis, source-to-target reconciliation, data validation and root cause analysis to ensure trusted, high-quality data.
  • AI-Assisted Engineering: Leverage approved Generative AI tools, GitHub Copilot and LLM-based solutions to accelerate code development, testing, troubleshooting, documentation and engineering automation.
  • Performance & Reliability: Optimize data-processing performance, automate monitoring, troubleshoot production issues and implement preventive measures to improve platform stability.
  • Data Product Enablement: Build reusable customer, product, campaign and engagement data capabilities supporting enterprise Marketing, targeting, personalization and analytics.
  • Engineering Excellence: Follow software engineering best practices, including CI/CD, GitHub, code reviews, automated testing, data governance and production-readiness controls.
  • Cross-Functional Collaboration: Partner with Product Owners, Business stakeholders, architects and upstream/downstream engineering teams to understand requirements, resolve dependencies and deliver business capabilities.
  • Continuous Improvement: Proactively identify opportunities for automation, technical debt reduction, AI adoption and engineering productivity improvements.

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