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EXL

Data Engineer

Reposted 12 Hours Ago
Remote or Hybrid
Hiring Remotely in United States
110K-130K Annually
Senior level
Remote or Hybrid
Hiring Remotely in United States
110K-130K Annually
Senior level
Design, build, and optimize scalable ETL/ELT data pipelines using Databricks and cloud platforms. Implement data quality checks, monitor and troubleshoot jobs, audit pipelines for compliance, and collaborate with analysts and business stakeholders to define data models and support reporting.
The summary above was generated by AI

Work Location: United States
Work Mode      : Remote
Pay Range       :$110K-$130K /Yr Base + Annual Bonus

 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


Job Overview:

We are seeking a skilled Data Engineer to join our team. The successful candidate will be responsible for development and optimization of data pipelines, implementing robust data checks, and ensuring the accuracy and integrity of data flows. This role is critical in supporting data-driven decision-making processes, especially in the context of our insurance-focused business operations

Responsibilities

Key Responsibilities:

  • Collaborate with data analysts, reporting team and business advisors to gather requirements and define data models that effectively support business requirements
  • Develop and maintain scalable and efficient data pipelines to ensure seamless data flow across various systems adddress any issues or bottlenecks in existing pipelines.
  • Implement robust data checks to ensure the accuracy and integrity of data. Summarize and validate large datasets to ensure they meet quality standards.
  • Monitor data jobs for successful completion. Troubleshoot and resolve any issues that arise to minimize downtime and ensure continuity of data processes.
  • Regularly review and audit data processes and pipelines to ensure compliance with internal standards and regulatory requirements
  • Familiar with working on Agile methodologies - scrum, sprint planning, backlog refinement etc.
Qualifications

Candidate Profile:

  • 7-12 years experience on Data Engineering role working with Databricks and any Cloud technologies- AWS , Azure , Databricks.
  • Bachelor’s degree in computer science, Information Technology, or related field.
  • Strong proficiency in PySpark, Python, SQL. 
  • Strong experience in data modeling, ETL/ELT pipeline development, and automation
  • Hands-on experience with performance tuning of data pipelines and workflows
  • Proficient in working on any cloud components Azure Data Factory, Azure DataBricks, Azure Data Lake , S3, Lamda.
  • Experience with data modeling, ETL processes, Delta Lake and data warehousing.
  • Experience on  Delta Live Tables, Autoloader & Unity Catalog. 
  • Preferred - Knowledge of the insurance industry and its data requirements.
  • Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
  • Excellent communication and problem-solving skills to work effectively with diverse teams
  • Excellent problem-solving skills and ability to work under tight deadlines.

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