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Tier-1 brand and metro Hyderabad increase competition, while niche Databricks/Iceberg skills moderate applicant density.
Core data engineering skills are transferable, but Databricks/Iceberg specialization raises domain specificity to medium.
Mandatory 6+ years plus specific Databricks, PySpark, Iceberg, SQL, and scripting requirements create high strictness.
Develop and optimize complex SQL Server backend processes including stored procedures and views to support analytical workloads.
Design and manage scalable ETL/ELT pipelines on Databricks using PySpark and Python for large-scale batch and near-real-time data processing.
Build and maintain Apache Iceberg tables and automate infrastructure tasks, including cluster performance tuning and deployment scripting.
6+ years of experience in data engineering or a similar role.
Proficient in SQL Server (T-SQL), query tuning, indexing, and complex SQL query development.
Hands-on experience with PySpark, Python, Databricks Workflows, and Apache Iceberg.
Experience working with cloud platforms (AWS or GCP).
Deep technical expertise bridging on-premise SQL Server environments with cloud-based lakehouse platforms (Databricks, Apache Iceberg).
Experienced in both development of data pipelines and operational automation including CI/CD and performance monitoring.
Skilled in collaboration with data scientists, analysts, and stakeholders to deliver reliable and governed data solutions.