Senior Data Engineer

Job Description: Design and develop ETL/ELT pipelines using Azure Data Factory, Snowflake, and DBT.

• Build and maintain data integration workflows from various data sources to Snowflake.
• Write efficient and optimized SQL queries for data extraction and transformation.
• Work with stakeholders to understand business requirements and translate them

into technical solutions.

• Monitor, troubleshoot, and optimize data pipelines for performance and reliability.
• Maintain and enforce data quality, governance, and documentation standards.
• Collaborate with data analysts, architects, and DevOps teams in a cloud-native environment.

Base Compensation Range: 90,000 - 110,000

The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position.

The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.

For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits

Responsibilities

Key Responsibilities:

• Design and develop ETL/ELT pipelines using Azure Data Factory, Snowflake,

and DBT.

• Build and maintain data integration workflows from various data sources to

Snowflake.

• Write efficient and optimized SQL queries for data extraction and transformation.
• Work with stakeholders to understand business requirements and translate them

into technical solutions.

• Monitor, troubleshoot, and optimize data pipelines for performance and

reliability.

• Maintain and enforce data quality, governance, and documentation standards.
• Collaborate with data analysts, architects, and DevOps teams in a cloud-native

environment.

Must-Have Skills:

• Strong experience with Azure Cloud Platform services.
• Proven expertise in Azure Data Factory (ADF) for orchestrating and automating

data pipelines.

• Proficiency in SQL for data analysis and transformation.
• Hands-on experience with Snowflake and SnowSQL for data warehousing.
• Practical knowledge of DBT (Data Build Tool) for transforming data in the

warehouse.

• Experience working in cloud-based data environments with large-scale datasets.

Good-to-Have Skills:

• Experience with Azure Data Lake, Azure Synapse, or Azure Functions.
• Familiarity with Python or PySpark for custom data transformations.
• Understanding of CI/CD pipelines and DevOps for data workflows.
• Exposure to data governance, metadata management, or data catalog tools.
• Knowledge of business intelligence tools (e.g., Power BI, Tableau) is a plus.

Qualifications:

• Bachelor’s or master’s degree in computer science, Data Engineering,

Information Systems, or a related field.

• 5+ years of experience in data engineering roles using Azure and Snowflake.

Key Skills

Azure, Snowflake, SQL, Data Factory, DBT

Qualifications: Qualifications:

• Bachelor’s or master’s degree in computer science, Data Engineering,

Information Systems, or a related field.