Design, build, and maintain ETL/ELT pipelines and data integration workflows to Snowflake using Azure Data Factory and DBT. Write optimized SQL, monitor and optimize pipeline performance, enforce data quality and governance, and provide technical leadership to junior engineers while collaborating with analysts, architects, and DevOps in cloud environments.
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.
- Provide technical leadership and mentorship to junior data engineers.
- 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 DataStage, Netezza, 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
ResponsibilitiesKey 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.
- Provide technical leadership and mentorship to junior data engineers.
- 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 DataStage, Netezza, 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
Qualifications:
- Bachelor’s degree in Data Engineering or a related field.
- 7+ years of experience in data engineering roles using Azure and Snowflake.
- Strong problem-solving, communication, and collaboration skills
Base Compensation Range: $100-135k
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.
About Us EXL (NASDAQ: EXLS) is a leading data analytics and digital operations and solutions company. We partner with clients using a data and AI-led approach to reinvent business models, drive better business outcomes and unlock growth with speed. EXL harnesses the power of data, analytics, AI, and deep industry knowledge to transform operations for the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 54,000 employees spanning six continents. For more information, visit www.exlservice.com.
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