Senior Data Engineer

JSR Tech Consulting

Belleville, NJ, United States

2 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

8 years minimum

Working hours

Regular working hours

Job source

www.disabledperson.com

Tech stack

Microsoft Access Application Programming Interfaces (APIs) Agile Methodology Airflow Amazon Web Services Amazon Elastic Compute Cloud Amazon S3 Data Analysis Automation of Tests Unit Testing Bash Shell Software Quality

+50 more

Code Review Computer Programming Continuous Integration Extract Transform Load (ETL) Data Systems Data Warehousing Relational Databases DevOps File Systems Amazon DynamoDB Gradle Groovy Identity and Access Management Python (Programming Language) Apache Maven Network Attached Storage (Server Appliance) Role-Based Access Control Standard Sql Shell Script Amazon Simple Notification Service (SNS) Software Engineering SONAR (Symantec) SonarQube SQL Stored Procedures Enterprise Data Management Cloudbees DevOps Tools - Open-source Delivery Pipeline Apache Spark Cloudformation Servicebus Amazon Relational Database Service Information Technology Data Lineage Atlassian Tools Production Code AWS Data Analytics Apache Kafka SAP Ariba Bitbucket Cloudwatch Restful APIs Amazon Simple Queue Service (SQS) Marketplace Software Version Control Data Pipelines Docker Jenkins Vulnerability Analysis Artifactory

Job description

Join a major investment firm as a Senior AWS Data Engineer supporting enterprise data platform initiatives. This role focuses on building scalable data pipelines, CI/CD automation, and end-to-end data solutions across the AWS ecosystem. Experience with Informatica (data catalogue, marketplace, data lineage, data quality), Denodo, and/or Ataccama is a strong plus., * Design, build, and maintain efficient, reusable, and reliable code

Ensure optimal performance and quality of high-scale data applications and services
Participate in system design discussions
Independently perform hands-on development and unit testing
Collaborate with the development team to integrate components into the enterprise data platform
Work cross-functionally with product, QE/QA, and other teams throughout the full software development lifecycle
Identify and resolve performance issues
Stay current with emerging technologies and implementation practices
Participate in code reviews to ensure standards and best practices are met
Take ownership of estimating, planning, and managing tasks in an Agile environment
Take shared responsibility for software quality rather than relying on separate QA teams
Collaborate closely with all team members toward shared goals
Engage with users as needed to clarify requirements

Requirements

Bachelor’s degree in Computer Science, Software Engineering, MIS, or equivalent combination of education and experience
8+ years of experience as a Data Engineer on the AWS stack, including DevOps tooling
AWS Solutions Architect or AWS Developer Certification required
Strong hands-on experience with AWS services, including:
CloudFormation, S3, Athena, Glue, Glue DataBrew, EMR/Spark
RDS, Redshift, DynamoDB, Lambda, Step Functions
IAM, KMS, SM, EventBridge, EC2, SQS, SNS
LakeFormation, CloudWatch, CloudTrail, DataSync, DMS
Experience implementing high-velocity streaming solutions using Amazon Kinesis, AWS Managed Airflow, and AWS Managed Kafka (preferred)
Proven experience building AWS data lake/data warehouse solutions
Skilled in designing, developing, and implementing data ingestion pipelines on AWS
Knowledge of ETL/ELT implementation for data solutions
Experience delivering end-to-end data solutions: ingest, storage, integration, processing, and access
Familiarity implementing RBAC strategies using AWS IAM and Redshift RBAC model
Experience building and implementing CI/CD pipelines using CloudFormation and Jenkins
Strong programming skills in Python, Shell scripting, and SQL
Experience with SQL stored procedures for data analysis
Experience building automated pipelines to ingest data from relational databases, file systems, and NAS shares into AWS RDS, Aurora, and Redshift
Experience building automated pipelines to ingest data from REST APIs into AWS S3 and relational databases
Solid DevOps background, including:
Bitbucket (source code management)
Python, Shell, Groovy scripting
API deployment for tooling integration
Jenkins and CloudBees (Pipeline as Code, Shared Libraries)
SonarQube, Artifactory, and similar DevOps tools
Maven, MS Build, Gradle
Docker
Jira and Confluence
Infrastructure as Code via CloudFormation
Experience creating Jenkins CI pipelines integrating Sonar/security scans and test automation
Ability to accurately document exceptions, issues, action plans, meeting minutes, and lessons learned