AWS Data Engineer

Description :

Urgent opening for AWS Data Engineers ( Remote)

Experience : 6+ years

Work timings : 1.00pm -10.00 p.m (Mon-Fri)

Contract duration : 3 months (can be extended)

Mandatory :

- AWS Data Engineering, AWS Services(AWS Glue, S3, Redshift, EMR, Lambda, Step Functions, Kinesis, Athena, and IAM).

- Python, PySpark, and Apache Spark,data modelling,on-prem/cloud data warehouse ,DevOps

Techstack Table :

- Cloud Platform AWS Data Engineering

- AWS Services Glue, S3, Redshift, EMR, Lambda, Step Functions, Kinesis, Athena, IAM

- Programming Python, PySpark, Apache Spark

- Data Management Data Modelling, On-Prem/Cloud Data Warehouse

- DevOps CI/CD, Automation, Deployment, Monitoring

Job Description :

We are seeking an experienced AWS Data Engineer with 6+ years of experience, strong understanding of large, complex, and multi-dimensional datasets. The ideal candidate will design, develop, and maintain scalable data pipelines and transformation frameworks using AWS native tools and modern data engineering technologies.

The role requires hands-on experience in AWS Data Engineering services and strong data modelling expertise. Exposure to Veeva API integration will be a plus (not mandatory).

Responsibilities :

- Design, develop, and optimize data ingestion, transformation, and storage pipelines on AWS.

- Manage and process large-scale structured, semi-structured, and unstructured datasets efficiently.

- Build and maintain ETL/ELT workflows using AWS native tools such as Glue, Lambda, EMR, and Step Functions.

- Design and implement scalable data architectures leveraging Python, PySpark, and Apache Spark.

- Develop and maintain data models and ensure alignment with business and analytical requirements.

- Work closely with stakeholders, data scientists, and business analysts to ensure data availability, reliability, and quality.

- Handle on-premises and cloud data warehouse databases and optimize performance.

- Stay updated with emerging trends and technologies in data engineering, analytics, and cloud computing.

Requirements :

- Mandatory: Proven hands-on experience with AWS Data Engineering stack, including but not limited to:

- AWS Glue, S3, Redshift, EMR, Lambda, Step Functions, Kinesis, Athena, and IAM.

- Proficiency in Python, PySpark, and Apache Spark for data transformation and processing.

- Strong understanding of data modelling principles and ability to design and maintain conceptual, logical, and physical data models.

- Experience working with one or more modern data platforms: Snowflake, Dataiku, or Alteryx (Good to have not mandatory)

- Familiarity with on-prem/cloud data warehouse systems and migration strategies.

- Solid understanding of ETL design patterns, data governance, and best practices in data quality and security.

- Knowledge of DevOps for Data Engineering CI/CD pipelines, Infrastructure as Code (IaC) using Terraform/CloudFormation (Good to have not mandatory)

- Excellent problem-solving, analytical, and communication skills.

Desirable candidate :

- Qualification - Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or a related field.

- Experience with cloud data engineering tools/components/technologies such as AWS Glue, EMR, S3 & EC2.

- Continual learning mindset to understand emerging trends in the data science field.