Sr Data Engineer

Overview

Hybrid
$60 - $65
Contract - W2
Contract - 12 Month(s)

Skills

Data Processing
Data Engineering
Data Modeling
Amazon RDS
Amazon Redshift
Amazon S3
Amazon Web Services
Analytics
Cloud Computing
Collaboration
DMS
Data Governance
Data Security
Data Warehouse
Electronic Health Record (EHR)
Extract
Transform
Load
HIPAA
IaaS
Management
Optimization
Performance Tuning
Privacy
PySpark
Python
Regulatory Compliance
Remote Desktop Services
Reporting
SQL
Snow Flake Schema
Streaming
Use Cases
Workflow

Job Details

Job Title: Senior Data Engineer

Location: MD, VA, DC (Preferred Onsite/Hybrid as required)

Experience Required: 10+ Years

Employment Type: Contract-W2

### Job Overview:

Client is seeking a highly experienced and hands-on Senior Data Engineer to lead the design and development of scalable data solutions. This role involves close collaboration with clients to gather requirements, build data pipelines, and deliver high-performing cloud-based architectures using AWS technologies.

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### Key Responsibilities:

Design, implement, and maintain batch and streaming data pipelines using Python, PySpark, and SQL.

Collaborate directly with clients and cross-functional teams to translate business needs into technical solutions.

Lead end-to-end development of data engineering workflows and ensure on-time delivery.

Build and manage scalable cloud-based data platforms using core AWS services such as:

AWS Glue, DMS, Step Functions

Amazon S3, RDS, Redshift, EMR, Lambda

AWS IAM, CloudWatch, CloudTrail

Develop optimized data models to support reporting and analytics use cases.

Manage and monitor data warehouse environments (Redshift or Snowflake).

Apply best practices for ETL design, including validation, error handling, and performance tuning.

Ensure data security, privacy, and compliance with industry regulations like HIPAA and GDPR.

Set up monitoring and alerting for pipeline reliability and system health.

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### Required Skills & Qualifications:

Minimum 10 years of hands-on data engineering experience.

Proven expertise in AWS data services and cloud infrastructure.

Strong knowledge of Python, PySpark, and SQL for data processing.

Experience with data modeling, ETL optimization, and performance tuning.

Ability to lead technical projects and collaborate effectively with both technical and non-technical stakeholders.

Familiarity with data governance, security best practices, and regulatory compliance standards.

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.