Data Engineer

Intellisoft Inc
Malvern, United States of America
3 days ago

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Malvern, United States of America

Tech stack

Airflow
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Business Analytics Applications
Apache HTTP Server
Big Data
Continuous Integration
Directed Acyclic Graph (Directed Graphs)
Information Engineering
Data Governance
ETL
Data Systems
Data Warehousing
Dimensional Modeling
Github
Hive
Identity and Access Management
Python
Performance Tuning
Query Optimization
Workflow Management Systems
Cloud Platform System
Delivery Pipeline
Snowflake
Electronic Medical Records
Cloudformation
Data Lake
PySpark
Semi-structured Data
Information Technology
Deployment Automation
Amazon Web Services (AWS)
Star Schema
Functional Programming
Cloudwatch
Terraform
Data Pipelines
Jenkins
Redshift
Databricks

Requirements

MUST HAVE 12 YEARS OF IT EXPERIENCE AND QUICK SIGHT EXPERIENCE

  • Senior Data Engineer with 12+ years of experience designing and delivering enterprise-scale data warehousing, ETL/ELT, and cloud-native analytics solutions using AWS Redshift, S3, Glue, Lambda, Airflow, PySpark, and Python.
  • Strong hands-on expertise with Amazon Redshift, including schema design, distribution keys, sort keys, query optimization, workload management, Redshift Spectrum integration, and performance tuning for large-scale analytical workloads.
  • Designed and implemented scalable ETL/ELT pipelines using AWS Glue, PySpark, Python, Airflow, Lambda, and S3, enabling efficient ingestion, transformation, and processing of high-volume structured and semi-structured data.
  • Extensive experience in advanced SQL development, data modeling, dimensional modeling (Star/Snowflake Schemas), data warehousing, and optimization of complex analytical queries supporting enterprise reporting and business intelligence.
  • Strong AWS experience with S3, Glue, Lambda, IAM, CloudWatch, EMR, Athena, EventBridge, and Redshift, building secure, scalable, and highly available cloud-based data platforms.
  • Developed and optimized large-scale data processing solutions using PySpark, Spark SQL, Databricks, and EMR, improving processing performance, scalability, and cost efficiency across enterprise data ecosystems.
  • Built and maintained Apache Airflow DAGs for workflow orchestration, scheduling, dependency management, monitoring, and automated recovery of complex data pipelines.
  • Experienced in modern Data Lake and Lakehouse architectures leveraging S3, Delta Lake, Apache Iceberg, Snowflake, and Databricks, supporting scalable analytics and data governance initiatives.
  • Implemented CI/CD and Infrastructure as Code solutions using Terraform, GitHub Actions, Jenkins, AWS CodePipeline, and CloudFormation, enabling automated deployment and management of data engineering workloads.
  • Proven ability to collaborate with cross-functional teams to deliver robust, high-performance data solutions that support analytics, reporting, operational intelligence, and business-critical decision-making.

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