Our client is seeking a Data Engineer with 5+ years of hands-on experience to build an AI-enablement layer on top of its enterprise Finance data platform. The role focuses on designing, building, and operating trusted datasets, semantic models, governed data products, and embedded natural-language analytics using Snowflake and/or Databricks.

This is a data platform engineering role, not a data science or model-building role. The successful candidate will build the governed data foundation that makes enterprise AI reliable, secure, and accessible to Finance business users.

Key Responsibilities

- Build AI-ready, governed data products on Snowflake and/or Databricks with clearly defined KPIs, hierarchies, and business semantics.
- Develop semantic layers and trusted datasets for BI reporting and natural-language querying.
- Configure and optimize Snowflake Cortex capabilities and/or Databricks Genie spaces for accuracy and business relevance.
- Build RAG pipelines and conversational analytics applications using Streamlit or Databricks Apps.
- Develop and maintain ETL/ELT pipelines using dbt, Airflow, Snowpark, PySpark, SQL, and Python.
- Implement data governance controls, including RBAC, row- and column-level security, masking, lineage, metadata management, and auditability.
- Collaborate with Finance stakeholders while optimizing platform performance, compute costs, and LLM usage.

Required Skills

- 5+ years of hands-on data engineering experience on cloud data platforms.
- Demonstrated real-world project delivery experience with Snowflake and/or Databricks.
- Direct hands-on experience building, configuring, and tuning Snowflake Cortex capabilities or Databricks Genie spaces with semantic models in production or advanced pilots.
- Proven experience delivering semantic layers and trusted, governed data products.
- Strong understanding of KPI definitions, business hierarchies, data semantics, and business glossary alignment.




- Solid hands-on expertise in dbt, PySpark, Snowpark, SQL, and Python.
- Experience with Airflow, Databricks Workflows, or an equivalent orchestration tool.
- Experience implementing data governance controls such as RBAC, row-level security, data masking, lineage, and auditability.
- Data governance experience within regulated enterprise environments.
- Experience integrating structured and unstructured data, including PDFs, SharePoint or Microsoft Teams content, and enterprise knowledge sources, into AI-enablement workflows.

Nice-to-Have Skills

- Experience in pharma, life sciences, regulated financial services, or another highly regulated domain.
- Experience integrating Veeva CRM, IQVIA, SAP, clinical data, or similar enterprise data sources.
- Experience building business-facing analytics applications using Streamlit or Databricks Apps.
- SnowPro Advanced or Databricks Data Engineer Professional certification.
- Experience with LangChain, LlamaIndex, or an equivalent RAG framework.
- Experience optimizing data-platform compute, including warehouse sizing, cluster tuning, and query performance.
- Knowledge of LLM cost optimization through token management, caching, and model routing.
- Familiarity with Finance data models, KPIs, reporting processes, and governance requirements.

About YMinds.AI

YMinds.AI is a technology-driven talent and consulting organization focused on connecting skilled professionals with opportunities in Artificial Intelligence, data engineering, cloud technologies, and digital transformation. We work with clients to build high-performing teams capable of delivering scalable, secure, and future-ready technology solutions.

Keywords

Data Engineer, Snowflake, Databricks, Snowflake Cortex, Databricks Genie, PySpark, SQL, Python, dbt, Airflow, ETL/ELT, RAG, Data Governance, Semantic Models

Hashtags

#DataEngineer #Snowflake #Databricks #DataEngineering #SnowflakeCortex #DatabricksGenie #HyderabadJobs #Hiring #YMindsAI

📌 Data Engineer – Snowflake/Databricks | 5+ Years | Hyderabad | Immediate Joiners Only
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