Lead Analytics Engineer

Posted 21 Days Ago
Hiring Remotely in United States
Remote
Senior level
Information Technology • Database • Consulting
The Role
Hands-on engineering role to design, build, and maintain scalable ETL/ELT data pipelines, data warehouses and lakes, and data models. Optimize batch and near-real-time processing, implement query optimization and data quality checks, support AI data workflows, and collaborate with architects, analysts, and stakeholders.
Summary Generated by Built In

This is a hands-on engineering role focused on designing efficient data pipelines, improving data infrastructure, and enabling teams to leverage data effectively.

Responsibilities
  • Design, build, and maintain scalable data pipelines and ETL/ELT workflows to ingest and transform data from multiple sources
  • Develop and optimize batch and near real-time data processing pipelines for analytics and reporting
  • Build and maintain data warehouse and data lake structures to support business intelligence and analytics use cases
  • Implement and maintain data models that support efficient querying and reporting
  • Improve performance and scalability of data systems through query optimization, indexing, and partitioning strategies
  • Implement data quality checks, monitoring, and logging to ensure reliability of data pipelines
  • Exposure to AI initiatives and experience building data pipelines supporting AI workflows 
  • Work with data architects and engineering teams to implement scalable data platform designs
  • Collaborate with analysts, BI developers, and business stakeholders to deliver data solutions that support business needs
  • Maintain documentation for data pipelines, data models, and data workflows
Qualifications

Bachelor's/Master's in Engineering 5-8 years

Skills Required

  • Bachelor's or Master's degree in Engineering
  • 5-8 years of relevant experience
  • Design, build, and maintain scalable data pipelines and ETL/ELT workflows
  • Experience developing and optimizing batch and near real-time data processing pipelines
  • Experience building and maintaining data warehouse and data lake structures
  • Experience implementing data models, query optimization, indexing, and partitioning strategies
  • Implementing data quality checks, monitoring, and logging for pipelines
  • Exposure to AI initiatives and building data pipelines supporting AI workflows
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The Company
HQ: New York, NY
30,246 Employees
Year Founded: 1999

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.

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