Cloud Data Engineer

Reposted 17 Days Ago
Hiring Remotely in United States
Remote
Senior level
Information Technology • Database • Consulting
The Role
Design, build, and optimize scalable AWS-based data pipelines, data lakes, and warehouses. Migrate legacy systems, enforce data quality/security/governance, implement ETL/ELT and big-data solutions, adopt CI/CD and IaC, collaborate with stakeholders, and provide technical leadership and troubleshooting.
Summary Generated by Built In

We are seeking an experienced AWS Data Engineer to join our Data Engineering team. You will be responsible for architecting, implementing, and managing scalable data solutions on AWS. Candidate would be required to work from NJ office as part of this role.

Responsibilities

design, development, and optimization of large-scale, reliable, and secure data pipelines and data lake architecture on AWS.
Architect and implement end-to-end data solutions, including data ingestion, storage, transformation, and analytics using AWS services (Glue, Redshift, S3, Lambda, EMR, Kinesis, Athena, RDS, etc.).
Collaborate with data scientists, analysts, and business stakeholders to translate requirements into scalable and maintainable solutions.
Oversee migration of data from legacy systems to AWS-based data lakes and data warehouses.
Develop and enforce standards for data quality, security, and governance.
Drive the adoption of DevOps, CI/CD, and infrastructure-as-code practices within the data engineering team.
Ensure solutions are cost-effective, performant, and aligned with enterprise data strategy.
Stay current with advancements in AWS technologies and data engineering trends and evaluate new tools and frameworks for potential adoption.
Troubleshoot complex data issues and provide technical leadership in problem resolution.

Qualifications

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
6+years of experience in data engineering.
Extensive hands-on experience with AWS data services (Glue, Redshift, S3, Lambda, EMR/Spark, Kinesis, Athena, RDS, API Gateway, etc.).
Proficient in programming languages such as Python and SQL; experience with Shell scripting and Scala is a plus.
Strong experience designing, implementing, and managing data lakes, data warehouses, and data ingestion pipelines on AWS.
Proven experience with ETL/ELT processes, data modeling, and big data frameworks.
Demonstrated ability to lead, mentor, and coach engineers in a collaborative team environment.
Experience with DevOps practices, CI/CD pipelines, and infrastructure-as-code tools (e.g., CloudFormation, Terraform).
Excellent problem-solving, communication, and organizational skills.
 

Preferred Qualifications:
AWS Solutions Architect or AWS Data Engineer certification.
Experience with real-time streaming technologies.
Knowledge of data governance, compliance, and security best practices.
Familiarity with Lakehouse architecture and modern data platforms.

Skills Required

  • Bachelor's or Master's degree in Computer Science, Engineering, or related field.
  • 6+ years of experience in data engineering.
  • Extensive hands-on experience with AWS data services (Glue, Redshift, S3, Lambda, EMR/Spark, Kinesis, Athena, RDS, API Gateway).
  • Proficient in Python and SQL.
  • Shell scripting experience.
  • Scala experience.
  • Strong experience designing, implementing, and managing data lakes, data warehouses, and data ingestion pipelines on AWS.
  • Proven experience with ETL/ELT processes, data modeling, and big data frameworks.
  • Demonstrated ability to lead, mentor, and coach engineers in a collaborative team environment.
  • Experience with DevOps practices, CI/CD pipelines, and infrastructure-as-code tools (CloudFormation, Terraform).
  • Excellent problem-solving, communication, and organizational skills.
  • AWS Solutions Architect or AWS Data Engineer certification.
  • Experience with real-time streaming technologies.
  • Knowledge of data governance, compliance, and security best practices.
  • Familiarity with Lakehouse architecture and modern data platforms.
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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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