▷ Urgent Search: DATA ENGINEER

2 weeks ago

Delhi, India Xorstack Full time

About Us: We are a dynamic and innovative company dedicated to delivering scalable and reliable data solutions for healthcare and ad-targeting industries. We thrive on harnessing the power of cloud-native technologies and advanced analytics to drive impactful business outcomes. Join our team to work on cutting-edge projects that leverage AI, big data, and cloud infrastructure.
Role Overview: We are looking for an experienced Data Engineer with a strong background in building and optimizing large-scale data pipelines within AWS cloud environments. This role requires expertise in ETL/ELT automation, Spark, Redshift, Glue, and orchestration tools like Airflow and Jenkins. The ideal candidate will be passionate about designing scalable data infrastructure, ensuring data quality, and improving pipeline performance.
Responsibilities:

Design, build, and maintain ETL/ELT pipelines using AWS Glue, Apache Spark, and PySpark for large-scale data processing.
Optimize data ingestion workflows from AWS S3 to Redshift and RDS to improve efficiency and reduce costs.
Develop data warehouses with fact and dimension tables tailored for analytical needs.
Automate and orchestrate data pipelines using Airflow and Jenkins for CI/CD integration.
Implement infrastructure as code using Terraform and automate deployments with Docker.
Lead end-to-end migration of data projects across AWS accounts ensuring zero data loss.
Monitor pipeline health and system uptime using Prometheus, Grafana, and AWS CloudWatch.
Collaborate with cross-functional teams to build analytics-ready datasets.
Innovate by leveraging AI-powered solutions like OpenAI API and Hugging Face models for query automation and unstructured data analysis.
Required Skills:

Minimum 3-6 years of experience as a Data Engineer with a strong focus on AWS services.
Proficiency in Python, SQL, Shell scripting, PySpark, and Apache Spark.
Hands-on experience with AWS Glue, Redshift, RDS, Lambda, S3, IAM, and other cloud services.
Familiarity with orchestration tools such as Apache Airflow and CI/CD pipelines with Jenkins or GitHub Actions.
Strong understanding of infrastructure provisioning using Terraform and containerization using Docker.
Experience implementing monitoring, logging, and alerting using Prometheus, Grafana, and Cloud Watch.
Knowledge of data modeling concepts including star and snowflake schemas.
Exposure to AI/ML model integration is a plus.
Qualifications:

Strong problem-solving skills and attention to detail.
Excellent communication and team collaboration abilities.

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