Azure Synapse + Data Warehouse - Sr Technical Lead-Data Engg

Birlasoft; Dadri; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

Birlasoft in India seeks an experienced Azure Synapse Performance Engineer to design, optimize, and troubleshoot enterprise-scale analytics platforms and data pipelines. You will drive end-to-end solutions across Synapse Analytics, ADF, and data lake architectures in a fast-paced data environment.

The role focuses on building high-performance ETL/ELT frameworks, optimizing SQL workloads, and ensuring scalability and reliability of data warehouses.

Qualifications

• Experience designing and optimizing Azure Synapse analytics solutions.
• Ability to build and optimize data integration using ADF and Synapse Pipelines.
• Strong SQL skills including tuning and execution plan analysis.

Responsibilities

• Design, develop, and optimize Azure Synapse Analytics solutions.
• Build and maintain data integration using Azure Data Factory (ADF) and Synapse Pipelines.
• Design scalable Data Lake architectures (ADLS Gen2).
• Develop high-performance ETL/ELT frameworks for enterprise data platforms.
• Monitor and troubleshoot large-scale data ingestion, transformation, and processing workloads.
• Identify performance bottlenecks and implement optimization strategies across data movement and transformation processes.
• Ensure data quality, availability, and reliability across analytics ecosystems.

Skills

Azure Synapse Analytics

Azure Data Factory

Synapse Pipelines

Azure Data Lake Storage Gen2

Azure SQL Database

Monitoring & Log Analytics

ETL/ELT Design

Data Modeling (Star/Snowflake)

Performance Tuning

Query Optimization

Partitioning & Indexing

Data Warehousing

Root Cause Analysis

Capacity Planning

Job description

Area(s) of responsibility

We are seeking an experienced Azure Synapse Performance Engineer with strong expertise in Azure Synapse Analytics, Azure Data Factory, ETL/ELT optimization, SQL performance tuning, and Data Warehouse architecture. The ideal candidate will be responsible for designing, optimizing, and troubleshooting enterprise-scale analytics platforms, data pipelines, and data warehouse workloads while ensuring high performance, scalability, and reliability. Similar responsibilities are referenced in internal documentation related to Azure Synapse, Data Lakes, ETL optimization, pipeline orchestration, and performance tuning.

Key Responsibilities

Azure Synapse & Data Engineering

• Design, develop, and optimize solutions using Azure Synapse Analytics.
• Build and maintain data integration solutions using Azure Data Factory (ADF) and Synapse Pipelines.
• Design and implement scalable Data Lake architectures (ADLS Gen2).
• Develop high-performance ETL/ELT frameworks for enterprise data platforms.
• Monitor and troubleshoot large-scale data ingestion, transformation, and processing workloads.
• Identify performance bottlenecks and implement optimization strategies across data movement and transformation processes.
• Ensure data quality, availability, and reliability across analytics ecosystems. These responsibilities align with internally referenced practices around data warehousing, ETL optimization, data lakes, and Synapse performance tuning. [25543668-c...3291332387 | Word]

SQL & Data Warehouse Performance

• Perform advanced SQL query analysis and optimization.
• Analyze and optimize execution plans for complex analytical workloads.
• Configure and tune Synapse Dedicated SQL Pools.
• Design and implement efficient partitioning strategies for large datasets.
• Optimize indexing, statistics, and workload distribution.
• Perform capacity planning and performance benchmarking.
• Support data warehouse modernization and optimization initiatives.

Required Technical Skills

Azure Technologies

• Azure Synapse Analytics
• Azure Data Factory (ADF)
• Synapse Pipelines
• Azure Data Lake Storage (ADLS Gen2)
• Azure SQL Database
• Azure Monitoring and Log Analytics

Data Engineering

• ETL/ELT Design and Development
• Data Lake Architecture
• Data Integration and Orchestration
• Batch and Incremental Data Processing
• Performance Tuning and Optimization

SQL & Data Warehousing

• Advanced T-SQL
• Query Performance Tuning
• Execution Plan Analysis
• Data Modeling (Star Schema / Snowflake Schema)
• Partitioning and Indexing Strategies
• Statistics Management
• Synapse SQL Pools
• Data Warehouse Optimization

Performance Engineering

• Root Cause Analysis
• Workload Monitoring
• Troubleshooting Large-Scale Data Processing
• Capacity Planning
• Performance Benchmarking