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EXL

Cloud Data Engineer

Posted Yesterday
Remote
Hiring Remotely in United States
Senior level
Remote
Hiring Remotely in United States
Senior level
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.
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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.

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