Data Engineer

Position : Data Engineer

Location : Princeton, NJ

• Day 1 Onsite

Duration : 1 Years

Mandatory Skills

Key Skills & Technologies

Programming Languages : Python (primary), SQL

Cloud Platforms : AWS (S3, Glue, Lambda, Redshift, EC2, EMR)

Data Tools : Apache Spark, Pandas, PySpark, Airflow

Databases : PostgreSQL, MySQL, NoSQL (e.g., DynamoDB)

ETL & Workflow Orchestration : AWS Glue, Apache Airflow

Version Control : Git

DevOps & CI / CD : Basic understanding of CI / CD pipelines and infrastructure as code (e.g., Terraform, CloudFormation)

JD

Data Pipeline Development - Design, build, and maintain scalable and reliable data pipelines to ingest, process, and transform data from various sources.

Data Integration & Management - Integrate structured and unstructured data from internal and external systems.

Ensure data quality, consistency, and availability across platforms.

Cloud-Based Data Engineering- Leverage AWS services (e.g., S3, Lambda, Glue, Redshift, EMR) to build cloud-native data solutions.

Optimize cloud resources for performance and cost-efficiency.

Programming & Automation - Use Python for data manipulation, ETL workflows, and automation of data tasks.

Develop reusable scripts and modules for data processing.

Collaboration & Stakeholder Engagement

Work closely with data scientists, analysts, and business teams to understand data needs.

Translate business requirements into technical solutions.

Monitoring & Optimization - Monitor data pipelines and troubleshoot issues proactively.

Continuously improve performance, scalability, and reliability of data systems.