Overview
Remote
$50 - $60
Contract - Independent
Contract - W2
Contract - 12 Month(s)
Skills
Apache Hadoop
Continuous Integration
Data Engineering
Data Governance
Data Lake
Data Modeling
Collaboration
Computer Science
Continuous Delivery
Data Analysis
Data Flow
Apache Kafka
Apache Spark
Big Data
Business Intelligence
Cloud Computing
Amazon Redshift
Data Quality
Data Security
Data Warehouse
Database Administration
Amazon Web Services
Apache Airflow
Electronic Health Record (EHR)
Extract
Transform
Load
Apache Hive
Data Processing
Google Cloud Platform
Informatica
Databricks
DevOps
Docker
ELT
Git
Good Clinical Practice
Management
Information Systems
Java
Kubernetes
MySQL
Oracle
PostgreSQL
Machine Learning (ML)
Meta-data Management
Python
RDBMS
Real-time
Microsoft Azure
Microsoft SQL Server
Privacy
Programming Languages
Regulatory Compliance
Agile
Amazon S3
SQL
Scala
Scalability
Snow Flake Schema
Talend
Unstructured Data
Version Control
Workflow
Job Details
Job Title: Senior Data Engineer (AWS + Azure) – Remote (USA)
Location: Remote (Anywhere in the USA)
Job Summary:
We are seeking an experienced Senior Data Engineer with strong expertise in AWS and Azure cloud environments to design, build, and maintain robust data solutions for enterprise-scale applications. The ideal candidate will have hands-on experience with data modeling, ETL/ELT pipelines, data warehousing, and cloud-based data lake architectures. This role requires someone who can take ownership of data engineering initiatives, collaborate with cross-functional teams, and drive cloud data strategies end-to-end.
Key Responsibilities:
- Design, develop, and maintain scalable data pipelines and architectures across AWS and Azure environments.
- Build and manage data ingestion, transformation, and integration frameworks using tools like ADF, Databricks, Glue, Lambda, and Synapse.
- Create and optimize data models for analytical and operational use cases (star, snowflake, and normalized schema designs).
- Manage data lakes, data warehouses, and streaming data platforms using services such as AWS Redshift, Azure Synapse, S3, ADLS, and Kafka/Kinesis.
- Work closely with Data Scientists, Analysts, and Architects to deliver business insights and ensure data integrity and performance.
- Implement and enforce best practices in data governance, security, quality, and compliance.
- Troubleshoot and optimize existing data systems for better performance and scalability.
- Contribute to the modernization of legacy data platforms to cloud-native solutions.
Required Skills & Experience:
- 8+ years of experience in Data Engineering or similar roles.
- Strong proficiency in both AWS and Azure data ecosystems.
- Hands-on experience with:
- AWS Glue, Redshift, Lambda, S3, Athena, EMR
- Azure Data Factory, Synapse Analytics, Databricks, ADLS, Event Hubs
- Strong SQL and Python programming skills for data manipulation and automation.
- Deep understanding of data modeling techniques, including OLAP/OLTP structures and schema design.
- Experience in ETL/ELT pipeline development and data orchestration (Airflow, Prefect, or similar).
- Experience working with Big Data tools (Spark, Hive, PySpark) and containerized deployments (Docker, Kubernetes).
- Familiarity with CI/CD pipelines and version control (Git, Azure DevOps, CodePipeline).
- Excellent communication, documentation, and analytical problem-solving skills.
Preferred Qualifications:
- Certifications such as:
- AWS Certified Data Analytics – Specialty
- Microsoft Certified: Azure Data Engineer Associate
- Experience with Power BI, QuickSight, or other visualization tools.
- Exposure to machine learning pipelines and data APIs.
- Experience working in Agile and DevOps environments.
Education:
- Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or related field.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.