icims
Senior Back End Developer
Intercontinental Exchange Holdings, Inc.
Hyderabad, IND
Full-time
Senior · 10+ years experience
Onsite
Discovered 1 weeks ago
SQL ServerT-SQLSSISPowerShellETL
Free
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Role Overview
We are looking for a talented and experienced Senior Data Engineer / Backend SQL Developer to join our Data Aggregation team.
In this role, you will be a core contributor to our SQL Server backend, writing complex stored procedures, views, and aggregation logic that feeds downstream reporting and analytical workloads.
Alongside traditional SQL Server development, you will extend these capabilities into the modern lakehouse using Python and Databricks, enabling scalable batch and near-real-time data processing across large datasets.
The ideal candidate brings deep expertise in SQL Server (T-SQL, stored procedures, query tuning, indexing strategies) combined with hands-on experience in PySpark, Apache Iceberg, and Databricks Workflows — and is comfortable bridging the gap between on-premise SQL environments and cloud-based data platforms.
Key Skills for This Role
SQL ServerT-SQLSSISPowerShellETL
Full Job Posting
Job Purpose
We are looking for a talented and experienced Senior Data Engineer / Backend SQL Developer to join our Data Aggregation team. In this role, you will be a core contributor to our SQL Server backend, writing complex stored procedures, views, and aggregation logic that feeds downstream reporting and analytical workloads. Alongside traditional SQL Server development, you will extend these capabilities into the modern lakehouse using Python and Databricks, enabling scalable batch and near-real-time data processing across large datasets. The ideal candidate brings deep expertise in SQL Server (T-SQL, stored procedures, query tuning, indexing strategies) combined with hands-on experience in PySpark, Apache Iceberg, and Databricks Workflows — and is comfortable bridging the gap between on-premise SQL environments and cloud-based data platforms.
Responsibilities
- Design and implement robust ETL/ELT pipelines using PySpark and Python on Databricks
- Build and manage Apache Iceberg table formats for efficient data storage, versioning, and time-travel queries on the data lakehouse
- Develop and optimize complex SQL queries, stored procedures, and data models for analytical workloads
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