EXL Service

AWS Senior Data Engineer

Jersey City, New Jersey, United States

Actively hiring, first seen by us today

Pay: Pay not listedSimilar roles state $127K–$190K
Work setting: Hybrid — work setting source
Work setup in the employer’s posting: Hybrid
From the employer’s posting
Employment: Not stated

What you’ll work on

Full posting

Build ingestion pipelines from on-prem systems and within AWS using Glue, Redshift, S3, Lambda and EMR
Develop and manage ETL/ELT processes that keep data accurate, secure and high quality
Architect end-to-end data solutions focused on data lakes and data warehouses
Build serverless applications with Lambda, API Gateway and Step Functions
Migrate data from relational databases, file systems and APIs into S3, RDS, Aurora and Redshift

From the employer’s posting

Build robust data ingestion pipelines (from on-prem to AWS and within AWS) using AWS services such as Glue, Redshift, S3, Lambda, EMR/Spark, Kinesis, and SQS.

Develop and manage ETL/ELT processes to collect, process, and store data from multiple sources, ensuring data quality, integrity, and security.

Architect and implement end-to-end data solutions (ingestion, storage, integration, processing, access) on AWS, with a focus on data lakes and data warehouses.

Implement serverless applications using AWS Lambda, API Gateway, Step Functions, and other AWS technologies.

Migrate data from traditional relational databases, file systems, and APIs to AWS-based data lakes (S3), RDS, Aurora, and Redshift.

What you’ll bring

All qualifications

Core experience

Bachelor’s degree in Computer Science, Software Engineering, MIS, or equivalent combination of education and experience.
8+ years of experience implementing and supporting data lakes, data warehouses, and data applications on AWS for large enterprises.
Solid experience with AWS services: CloudFormation, S3, Athena, Glue, EMR/Spark, RDS, Redshift, DynamoDB, Lambda, Step Functions, IAM, KMS, Secrets Manager.
Experience in serverless application development and data pipeline orchestration.
Experience in system analysis, design, development, and implementation of data ingestion pipelines in AWS.
Knowledge of ETL/ELT, data modeling, and big data technologies.

Preferred experience

Experience with additional AWS services: API Gateway, ElasticSearch, SQS.
Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation).
Experience with DevOps practices and CI/CD pipelines.
Experience implementing end-to-end streaming solutions (Amazon Kinesis, SQS, Kafka).

Qualification wording

Bachelor’s degree in Computer Science, Software Engineering, MIS, or equivalent combination of education and experience.

8+ years of experience implementing and supporting data lakes, data warehouses, and data applications on AWS for large enterprises.

Solid experience with AWS services: CloudFormation, S3, Athena, Glue, EMR/Spark, RDS, Redshift, DynamoDB, Lambda, Step Functions, IAM, KMS, Secrets Manager.

Experience in serverless application development and data pipeline orchestration.

Experience in system analysis, design, development, and implementation of data ingestion pipelines in AWS.

Knowledge of ETL/ELT, data modeling, and big data technologies.

Experience with additional AWS services: API Gateway, ElasticSearch, SQS.

Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation).

Experience with DevOps practices and CI/CD pipelines.

Experience implementing end-to-end streaming solutions (Amazon Kinesis, SQS, Kafka).

Education & alternatives

Required Qualifications: - Bachelor’s degree in Computer Science, Software Engineering, MIS, or equivalent combination of education and experience. - 8+ years of experience implementing and supporting data lakes, data warehouses, and data applications on AWS for large enterprises.

Apply at EXL Service

Posting record

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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records: Live
First seen by us: Nov 3, 2026today
Recorded sightings: 2
Last seen by us: Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$127K–$190K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 2,133 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 5 and day 54.

From 10,703 similar postings that came down. Coming down is not always a hire.

EXL Service is hiring

200 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Takes jobs down at a usual pace
5% of open jobs were reposted

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

Python
SQL
AWS
DynamoDB
Elasticsearch
Kafka
Redshift
S3
Spark
Terraform

Where the posting names them

- 8+ years of experience implementing and supporting data lakes, data warehouses, and data applications on AWS for large enterprises. - Strong programming experience with Python, Shell scripting, and SQL. - Solid experience with AWS services: CloudFormation, S3, Athena, Glue, EMR/Spark, RDS, Redshift, DynamoDB, Lambda, Step Functions, IAM, KMS, Secrets Manager.

We are seeking a talented AWS Data Engineer to join our dynamic Data Engineering team. The ideal candidate will be responsible for designing, developing, and maintaining scalable data pipelines and architectures in the AWS cloud environment. This role will collaborate closely with data scientists, analysts, and other business stakeholders to deliver robust data solutions. Base Compensation Range: 150,000 - 170,000

Key Responsibilities: - Design, build, and maintain efficient, reusable, and reliable architecture and code for data pipelines and data applications on AWS. - Build robust data ingestion pipelines (from on-prem to AWS and within AWS) using AWS services such as Glue, Redshift, S3, Lambda, EMR/Spark, Kinesis, and SQS.

- Design, build, and maintain efficient, reusable, and reliable architecture and code for data pipelines and data applications on AWS. - Build robust data ingestion pipelines (from on-prem to AWS and within AWS) using AWS services such as Glue, Redshift, S3, Lambda, EMR/Spark, Kinesis, and SQS. - Develop and manage ETL/ELT processes to collect, process, and store data from multiple sources, ensuring data quality, integrity, and security.

- Develop and manage ETL/ELT processes to collect, process, and store data from multiple sources, ensuring data quality, integrity, and security. - Architect and implement end-to-end data solutions (ingestion, storage, integration, processing, access) on AWS, with a focus on data lakes and data warehouses. - Participate in the architecture and system design discussions for high-scale data engineering projects.

- Independently perform hands-on development, unit testing, and participate in code reviews to ensure adherence to best practices. - Implement serverless applications using AWS Lambda, API Gateway, Step Functions, and other AWS technologies. - Migrate data from traditional relational databases, file systems, and APIs to AWS-based data lakes (S3), RDS, Aurora, and Redshift.

- Implement serverless applications using AWS Lambda, API Gateway, Step Functions, and other AWS technologies. - Migrate data from traditional relational databases, file systems, and APIs to AWS-based data lakes (S3), RDS, Aurora, and Redshift. - Implement high-velocity streaming solutions using Amazon Kinesis, SQS, and Kafka (preferred).

- Bachelor’s degree in Computer Science, Software Engineering, MIS, or equivalent combination of education and experience. - 8+ years of experience implementing and supporting data lakes, data warehouses, and data applications on AWS for large enterprises. - Strong programming experience with Python, Shell scripting, and SQL.

- Strong programming experience with Python, Shell scripting, and SQL. - Solid experience with AWS services: CloudFormation, S3, Athena, Glue, EMR/Spark, RDS, Redshift, DynamoDB, Lambda, Step Functions, IAM, KMS, Secrets Manager. - Experience in serverless application development and data pipeline orchestration.

- Experience in serverless application development and data pipeline orchestration. - Experience in system analysis, design, development, and implementation of data ingestion pipelines in AWS. - Knowledge of ETL/ELT, data modeling, and big data technologies.

Preferred Qualifications: - Experience with additional AWS services: API Gateway, ElasticSearch, SQS. - Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation).

- Experience implementing end-to-end streaming solutions (Amazon Kinesis, SQS, Kafka). - AWS Solutions Architect or AWS Developer Certification preferred. - Understanding of Lakehouse/data cloud architecture.

- Migrate data from traditional relational databases, file systems, and APIs to AWS-based data lakes (S3), RDS, Aurora, and Redshift. - Implement high-velocity streaming solutions using Amazon Kinesis, SQS, and Kafka (preferred). - Architect and implement CI/CD strategies for enterprise data platforms.

- Experience with DevOps practices and CI/CD pipelines. - Experience implementing end-to-end streaming solutions (Amazon Kinesis, SQS, Kafka). - AWS Solutions Architect or AWS Developer Certification preferred.

- Experience with additional AWS services: API Gateway, ElasticSearch, SQS. - Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation). - Experience with DevOps practices and CI/CD pipelines.

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Job description

View original posting ↗

We are seeking a talented AWS Data Engineer to join our dynamic Data Engineering team. The ideal candidate will be responsible for designing, developing, and maintaining scalable data pipelines and architectures in the AWS cloud environment. This role will collaborate closely with data scientists, analysts, and other business stakeholders to deliver robust data solutions.

Base Compensation Range: 150,000 - 170,000

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

Key Responsibilities:

Design, build, and maintain efficient, reusable, and reliable architecture and code for data pipelines and data applications on AWS.
Build robust data ingestion pipelines (from on-prem to AWS and within AWS) using AWS services such as Glue, Redshift, S3, Lambda, EMR/Spark, Kinesis, and SQS.
Develop and manage ETL/ELT processes to collect, process, and store data from multiple sources, ensuring data quality, integrity, and security.
Architect and implement end-to-end data solutions (ingestion, storage, integration, processing, access) on AWS, with a focus on data lakes and data warehouses.
Participate in the architecture and system design discussions for high-scale data engineering projects.
Independently perform hands-on development, unit testing, and participate in code reviews to ensure adherence to best practices.
Implement serverless applications using AWS Lambda, API Gateway, Step Functions, and other AWS technologies.
Migrate data from traditional relational databases, file systems, and APIs to AWS-based data lakes (S3), RDS, Aurora, and Redshift.
Implement high-velocity streaming solutions using Amazon Kinesis, SQS, and Kafka (preferred).
Architect and implement CI/CD strategies for enterprise data platforms.
Collaborate with product, operations, QA, and cross-functional teams throughout the software development cycle.
Stay abreast of new technology developments, implement POCs for new tools/technologies, and onboard them for real-world use cases.
Identify and resolve performance issues and continuously optimize for cost, reliability, and scalability.
Oversee organizational data engineering solutions. Lead highimpact initiatives. Ensure alignment with organizational goals. Provide executive guidance.

Required Qualifications:
Bachelor’s degree in Computer Science, Software Engineering, MIS, or equivalent combination of education and experience.
8+ years of experience implementing and supporting data lakes, data warehouses, and data applications on AWS for large enterprises.
Strong programming experience with Python, Shell scripting, and SQL.
Solid experience with AWS services: CloudFormation, S3, Athena, Glue, EMR/Spark, RDS, Redshift, DynamoDB, Lambda, Step Functions, IAM, KMS, Secrets Manager.
Experience in serverless application development and data pipeline orchestration.
Experience in system analysis, design, development, and implementation of data ingestion pipelines in AWS.
Knowledge of ETL/ELT, data modeling, and big data technologies.
Familiarity with data warehousing concepts and cloud-based architecture.
Strong problem-solving skills and attention to detail.
Excellent communication and teamwork abilities.

Preferred Qualifications:
Experience with additional AWS services: API Gateway, ElasticSearch, SQS.
Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation).
Experience with DevOps practices and CI/CD pipelines.
Experience implementing end-to-end streaming solutions (Amazon Kinesis, SQS, Kafka).
AWS Solutions Architect or AWS Developer Certification preferred.
Understanding of Lakehouse/data cloud architecture.
Knowledge of data governance and compliance standards.

Graduate in Computer Science, Data Science, or related field. 6-8 years of experience in data engineering or related field.

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