AWS Data Engineer

Robotic Process Automation LLC; New Jersey; On-site; USD 140,000 - 170,000; Full time

Job summary

Robotic Technologies Automation is seeking an AWS Data Engineer to design, develop, and maintain scalable data pipelines in AWS. You will work with data scientists, analysts, and business stakeholders to deliver robust data solutions and enable data-driven decisions.

The role requires 8+ years of experience, strong Python and PySpark skills, and deep AWS expertise to implement data lakes, data warehouses, and streaming solutions. Collaboration across teams and a proactive mindset are essential.

Qualifications

• 8+ years of experience implementing 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.

Responsibilities

• Design, build, and maintain data pipelines and applications on AWS.
• Build ingestion pipelines from on-prem to AWS and within AWS using Glue, Redshift, S3, Lambda, EMR/Spark, Kinesis, and SQS.
• Develop ETL/ELT processes to collect, process, and store data from multiple sources with quality and security.
• Architect end-to-end data solutions with a focus on data lakes and data warehouses.
• Participate in architecture discussions for high-scale data projects.
• Hands-on development, unit testing, and code reviews.
• Implement serverless apps using Lambda, API Gateway, Step Functions, etc.
• Migrate data to AWS data lakes (S3), RDS, Aurora, Redshift.
• Implement streaming solutions with Kinesis, SQS, Kafka.
• Design CI/CD strategies for enterprise data platforms.
• Collaborate with product, operations, QA, and cross-functional teams.

Skills

Team collaboration

Problem solving

Communication

Adaptability

Education

Bachelor’s degree in Computer Science or related field

Tools

Python

PySpark

AWS

S3

Redshift

Glue

Kinesis

Job description

Minimum of 8 years of experience. Strong AWS, Python, and PySpark experience.

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.

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.

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.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, and discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.