Senior Data Engineer

Posted Yesterday
Be an Early Applicant
Hiring Remotely in United States
Remote or Hybrid
100K-135K Annually
Senior level
Information Technology • Database • Consulting
The Role
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.
Summary Generated by Built In

Key Responsibilities: 

  • Design and develop ETL/ELT pipelines using Azure Data FactorySnowflake, 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 LakeAzure 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 governancemetadata management, or data catalog tools. 

Knowledge of business intelligence tools (e.g., Power BI, Tableau) is a plus

Responsibilities

Key Responsibilities: 

  • Design and develop ETL/ELT pipelines using Azure Data FactorySnowflake, 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 LakeAzure 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 governancemetadata 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.


EXL never requires or asks for fees/payments or credit card or bank details during any phase of the recruitment or hiring process and has not authorized any agencies or partners to collect any fee or payment from prospective candidates. EXL will only extend a job offer after a candidate has gone through a formal interview process with members of EXL’s Human Resources team, as well as our hiring managers.
About the TeamEXL is the indispensable partner for leading businesses in data-led industries such as insurance, banking and financial services, healthcare, retail and logistics. We bring a unique combination of data, advanced analytics, digital technology and industry expertise to help our clients turn data into insights, streamline operations, improve customer experience, and transform their business. Our partnerships with clients are built on a foundation of collaboration – and we’ve been chosen as a partner by nine of the top ten leading US insurance companies, nine of the top 20 global banks, and six of the top ten US health care payers. We function as one team to make your goals our goals, whether that’s unlocking the value of generative AI or embedding analytics into workflows that reduce risk or power your growth. Clients choose EXL as their transformation partner for many reasons. Our geographic diversity make talent all over the world instantly accessible. Digital accelerators enable unmatched speed-to-value, letting you realize results fast. It’s our people that truly set us apart, though, including the 1,500 data scientists we have dedicated to our generative AI practice. And our more than twenty years of experience in delivering business services, garnering stellar client references, and maintaining a solid balance sheet are reassuring to our C-suite clients. Find out for yourself why clients, employees, and analysts think we’re some of the best in the business. Contact us to see how we can help you achieve your goals.

Skills Required

  • Strong experience with Azure Cloud Platform services
  • Proven expertise in Azure Data Factory (ADF)
  • Proficiency in SQL for data analysis and transformation
  • Hands-on experience with Snowflake and SnowSQL
  • Practical knowledge of DBT (Data Build Tool)
  • Experience working in cloud-based data environments with large-scale datasets
  • 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
  • Familiarity with Python or PySpark for custom data transformations
  • Experience with DataStage and Netezza
  • Experience with Azure Data Lake, Azure Synapse, or Azure Functions
  • 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 (Power BI, Tableau)
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