Advanced Engineer Data

Role Summary:

- Design, build, and manage scalable data processing pipelines on the Google Cloud Platform.
- Drive engineering excellence, data quality, and continuous improvement.

Key Responsibilities:

- Lead end-to-end design, development, and deployment of scalable data pipelines and integration solutions.
- Manage multiple delivery workstreams.
- Translate complex business and technical requirements into robust data engineering solutions.
- Develop and optimize ETL/ELT processes using modern cloud, data warehousing, and data processing platforms.
- Collaborate with technical and business teams to translate complex requirements into robust data solutions.
- Diagnose and resolve complex production issues through root-cause analysis and system optimization.
- Drive technology and process improvements by evaluating emerging tools and engineering best practices.
- Ensure adherence to enterprise architecture, security, compliance, and performance standards.
- Maintain high-quality technical documentation, user guides, and solution specifications.

Required Qualifications:

Experience:

- Experience in Data modelling, Data engineering, Data integration.
- Experience leading engineering initiatives.
- Proven experience with cloud tools such as GCP Dataflow, GCP Composer (Airflow), GCP cloud storage.
- Strong expertise in cloud platforms: GCP
- Hands-on experience with data warehousing and processing technologies including:
- Experience with data streaming tools: Kafka, Cloud Data Flow, Spark Streaming.




- Strong experience in data quality and observability platforms to automate quality coverage using iceDQ, Monte Carlo, or similar tools.
- Solid proficiency with high-level programming and query languages.
- Experience collaborating with distributed teams across time zone.
- Big Query, Lakehouse (Iceberg)
- Spark
- Python, SQL

AI Skills (Mandatory):

- Proficiency in leveraging AI tools for daily engineering tasks to enhance productivity, optimize effort, and ensure cost-aware AI assistance.
- Familiarity with Retrieval Augmented Generation (RAG) architectures, including semantic layers for data retrieval and grounding Large Language Model (LLM) responses.
- Conceptual understanding of LLM-based applications (e.g., chatbots, Q&A; systems), encompassing prompt engineering, context management, and response generation.
- Exposure to agentic and multi-agent AI systems, including agent roles, tool utilization, memory management, and workflow orchestration.
- Practical experience with LLM application frameworks (e.g., LangChain, Lang Graph, or Google GenAI tools) for prototyping and integrating AI-driven solutions.

Nice to Have:

- Experience with Power BI/ThoughtSpot, AI in data engineering, Stonebranch, CI/CD, Databricks and DevOps practices.
- Familiarity with enterprise databases such as DB2, SQL Server, Oracle, PostgreSQL.
- Google Cloud Data Engineer certification is preferred.
- Experience in Retail domains (Customer, Stores, eCommerce, Marketing, Supply chain, Merchandising)

📌 Advanced Engineer Data (Bengaluru)
🏢 Albertsons Companies India
📍 Bengaluru