Lead Analytics Engineer

EXL Talent Acquisition Team; United States; Remote; USD 120,000 - 160,000; Full time

Job summary

EXL Talent Acquisition Team is seeking a hands-on data engineering professional for a remote, senior-level role focused on building and optimizing data pipelines and analytics infrastructure. You will design ETL/ELT workflows, data models, and scalable platforms to empower BI and AI initiatives across multiple sources.

The ideal candidate has 6–9 years of experience in engineering, with strong SQL, data warehousing, and performance tuning skills.

Qualifications

• Bachelor's or Master's degree in Engineering.
• 6–9 years of relevant experience.

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.

Skills

Data pipelines

ETL/ELT

Data modeling

SQL

Batch processing

Real-time processing

Data quality

Monitoring

Logging

AI data pipelines

Education

Bachelor's/Master's in Engineering

Tools

SQL

ETL Tools

Data Warehousing

Job description

• Experience (In Years) 6-9
• Job Location Remote

Job Description

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