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Metro location and general Data Engineer title increase competition, but senior 10+ years and niche lakehouse skills limit applicant pool.
Role demands deep lakehouse and Databricks on Azure skills but industry research knowledge requirement reduces transferability.
Explicit 10+ years plus mandatory Databricks, Azure, Iceberg, Unity Catalog and domain experience.
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Define, design, and govern enterprise data architecture supporting analytics, reporting, and AI/ML initiatives.
Architect and implement enterprise-scale data Lakehouse solutions using Databricks, DBT, Unity Catalog, Iceberg, and Azure cloud-native services.
Lead design and oversight of data ingestion, modeling, governance, pipeline frameworks, and ensure data architecture aligns with scalability, security, and performance standards.
10+ years of experience in data architecture, data engineering, and cloud data platforms with strong proficiency in Azure services.
Exposure to Secondary Market Research is mandatory.
Bachelor’s degree in Computer Science, Information Technology, or a similar quantitative field.
Fluent in English. Location: Hyderabad-based (implied by job location).
Proven expertise architecting enterprise lakehouse solutions using Databricks and Apache Iceberg.
Experience with advanced data modeling techniques (dimensional modeling, Data Vault, Data Mesh) and cloud data engineering tools (Azure Data Factory, Databricks Workflows, Apache Airflow, dbt).
Strong experience working with diverse enterprise data sources (SAP ERP, Salesforce CRM, Workday, cloud storage) and driving architectural decisions in cross-functional teams.