Title: AWS Data Engineer
Location: Newark, NJ (Hybrid)
Duration: 12 Months
Job Description:
Responsibilities:
- Designing, building, and maintaining efficient, reusable, and reliable code
- Ensure the best possible performance and quality of high scale data applications and services
- Participate in system design discussions
- Independently perform hands on development and unit testing of the applications
- Collaborate with the development team and build individual components into enterprise data platform
- Work in a team environment with product, QE/QA, and cross functional teams to deliver a project throughout the whole software development cycle.
- Responsible to identify and resolve any performance issues
- Keep up to date with new technology development and implementation
- Participate in code review to make sure standards and best practices are met
- Project management: Agile developers take responsibility for estimating, planning, and managing all tasks and report on progress
- Software quality: The Agile developer is also responsible for the quality of the software he/she produces. The team takes responsibility for the quality of the work they produce instead of turning over some code to a separate and independent group for testing
- Teamwork: This includes collaboration with all other team members with the aim to take shared responsibility for the overall efforts
- Understanding user needs: This is about interacting with users as necessary to clarify requirements
Primary & Must-Have Skills
- AWS Core Ecosystem: Glue, Lambda, S3, IAM Roles, Redshift, RDS.
- Infrastructure as Code (IaC): Writing CloudFormation templates.
- DevOps / CI-CD: GitHub repository version control, Jenkins, SonarQube, and X-Ray.
- Programming & Data Languages: Expert-level proficiency in Python (for Lambda) and SQL queries.
Nice-to-Have Ecosystem Tools
- Candidates will build integrations between these ecosystem tools using the AWS tech stack. Prior familiarity with any of the following is a major plus:
- Informatica: Specifically Data Catalog, Data Lineage, and Data Marketplace.
- Denodo: For data virtualization and data semantics.
- Ataccama: For Master Data Management (MDM), Reference Data Management (RDM), and data quality observability.
Background & Experience Profile
- Years of Experience: Around 8+ years of experience (Senior level).
- AWS Certifications: While strong experience is evaluated, certifications are highly preferred because they ensure a 360-degree visibility of AWS services for architectural design optimizations.
Qualifications:
- Bachelor's degree in Computer Science, Software Engineering, MIS or equivalent combination of education and experience
- 8+ years of experience as Data Engineer on AWS Stack with experience on DevOps tool
- AWS Solutions Architect or AWS Developer Certification required
- Solid experience of AWS services such as CloudFormation, S3, Athena, Glue, Glue DataBrew, EMR/Spark, RDS, Redshift, DataSync, DMS, DynamoDB, Lambda, Step Functions, IAM, KMS, SM, EventBridge, EC2, SQS, SNS, LakeFormation, CloudWatch, Cloud Trail
- Implement high velocity streaming solutions and orchestration using Amazon Kinesis, AWS Managed Airflow and AWS Managed Kafka (preferred)
- Solid experience building solutions on AWS data lake/data warehouse
- Analyze, design, development, and implementation of data ingestion pipeline in AWS
- Knowledge implementing ETL/ELT for data solutions
- End-to-end data solutions (ingest, storage, integration, processing, access) on AWS
- Knowledge implementing RBAC strategy/solutions using AWS IAM and Redshift RBAC model
- Build & implement CI/CD pipelines for EDP Platform using CloudFormation and Jenkins
- Programming experience with Python, Shell scripting and SQL
- Knowledge of analyzing data using SQL Stored procedures
- Build automated data pipelines to ingest data from relational database systems, file systems, NAS shares to AWS relational databases such as Amazon RDS, Aurora, and Redshift
- Build Automated data pipelines to ingest data from Rest APIs to AWS data lake (S3) and relational databases such as Amazon RDS, Aurora, and Redshift.
- Good Experience of DevOps practice
- Experience with modern source code management and software repository systems (Bitbucket)
- Experience with programming languages (Python)
- Experience with scripting languages (Shell, Groovy)
- Experience with API deployment for tooling integration
- Experience using Jenkins, CloudBees (Pipeline as Code, Shared Libraries)
- The ability to document exceptions/issues/action plans/meeting minutes/lessons learned accurately and in a timely fashion
- Experience with administering DevOps tools in SaaS
- Experience using DevOps Tools (SonarQube, Artifactory etc.)
- Experience using build tools (Maven, MS Build and Gradle)
- Experience using containers (Docker)
- Experience using Atlassian suite (Jira, Confluence)
- Experience of Infrastructure as Code using CloudFormation
- Creating Jenkins CI pipelines to integrate Sonar/Security scans and test automation scripts
- Part of DevOps QA and AWS team focusing on building CI/CD pipeline
- Responsible for writing and maintaining Jenkins Pipelines
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