Data Engineers design and build data systems and pipelines. Responsibilities include developing data processing workflows, optimizing data storage, and ensuring data accuracy. You will collaborate with data scientists and analysts to meet data requirements and resolve data issues. Strong experience in data engineering and problem-solving skills are required.
ResponsibilitiesDesign and implement data pipelines, Optimize data processing and storage, Ensure data solutions meet performance standards, Provide technical support, Collaborate with stakeholders.
Qualifications8+ years in data engineering/ETL roles, with at least 4+ years in Azure cloud ETL leadership. Azure certifications (e.g., Azure Analytics Specialty, Solutions
Required Qualifications:
- Azure Data Sources: Azure Data Lake Storage (ADLS), Blob Storage, Azure SQL Database, Synapse Analytics. External Sources: APIs, on-prem databases, flat files (CSV, Parquet, JSON).
- Tools: Azure Data Factory (ADF) for orchestration, Databricks connectors.
- Apache Spark: Strong knowledge of Spark (PySpark, Spark SQL) for distributed processing.
- Data Cleaning & Normalization: Handling nulls, duplicates, schema evolution.
- Performance Optimization: Partitioning, caching, broadcast joins.
- Delta Lake: Implementing ACID transactions, time travel, and schema enforcement.
- Azure Data Factory (ADF): Building pipelines to orchestrate Databricks notebooks.
- Azure Key Vault: Secure credential management.
- Azure Monitor & Logging: For ETL job monitoring and alerting.
- Networking & Security: VNET integration, private endpoints.
Skills Required
- 8+ years in data engineering/ETL roles
- 4+ years in Azure cloud ETL leadership
- Azure certifications (e.g., Azure Analytics Specialty)
- Azure Data Lake Storage (ADLS)
- Azure Blob Storage
- Azure SQL Database
- Synapse Analytics
- APIs and on-prem databases integration experience
- Flat file handling: CSV, Parquet, JSON
- Azure Data Factory (ADF) for orchestration
- Databricks and Databricks connectors
- Apache Spark (PySpark, Spark SQL)
- Delta Lake (ACID transactions, time travel, schema enforcement)
- Data cleaning and normalization (nulls, duplicates, schema evolution)
- Performance optimization (partitioning, caching, broadcast joins)
- Azure Key Vault for secure credential management
- Azure Monitor and logging for ETL monitoring and alerting
- Networking & security: VNET integration and private endpoints
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.
