Senior Data Engineer

Overview

Hybrid
70 - 80
Contract - W2
Contract - 12 Month(s)
No Travel Required
Unable to Provide Sponsorship

Skills

Cloud Computing
Amazon Redshift
Amazon Web Services
Artificial Intelligence
Conflict Resolution
Big Data
Collaboration
Data Engineering
Data Flow
Data Security
Data Governance
Databricks
Docker
Data Integration
Data Lake
Communication
Computer Science
Continuous Delivery
Continuous Integration
Analytical Skill
Analytics
Apache Hadoop
Apache Kafka
Apache Spark
Electronic Health Record (EHR)
Regulatory Compliance
Machine Learning (ML)
Microsoft Azure
Problem Solving
Real-time
Git
Good Clinical Practice
Google Cloud Platform
Kubernetes
Python
Data Modeling
Data Quality
Data Warehouse
Extract, Transform, Load
Finance
Reporting
SQL
Scalability
Snow Flake Schema
Streaming
Teamwork
Telecommunications
Unstructured Data
Version Control
Workflow
ELT

Job Details

Job Title: Senior Data Engineer
Employment Type: W2
Experience Level: 10+ Years

About the Role
We are seeking a highly skilled Senior Data Engineer to design, build, and optimize scalable data pipelines and architectures for enterprise analytics and AI/ML initiatives. The ideal candidate will have deep expertise in modern data platforms, big data tools, and cloud technologies, with strong problem-solving and collaboration skills.

Key Responsibilities

  • Design, develop, and maintain large-scale data pipelines, ETL/ELT processes, and data integration frameworks.

  • Work with structured and unstructured data from multiple sources.

  • Build and optimize data models to support analytics, reporting, and machine learning.

  • Implement data quality, data governance, and security best practices.

  • Collaborate with data scientists, analysts, and application developers to ensure efficient data flow and accessibility.

  • Monitor, troubleshoot, and optimize data workflows for performance and scalability.

  • Evaluate and integrate emerging data technologies and cloud services.

Required Skills & Qualifications

  • 8–12+ years of experience as a Data Engineer or related role.

  • Strong proficiency in SQL, Python, and ETL/ELT development.

  • Expertise in one or more cloud data platforms – AWS (Glue, Redshift, EMR), Azure (Data Factory, Synapse, Databricks), or Google Cloud Platform (BigQuery, Dataflow).

  • Experience with big data technologies such as Apache Spark, Hadoop, or Kafka.

  • Solid understanding of data warehousing, data modeling, and data lake architectures.

  • Familiarity with CI/CD, version control (Git), and containerization (Docker, Kubernetes).

  • Excellent analytical, communication, and teamwork skills.

Preferred Qualifications

  • Experience with Databricks, Airflow, or Snowflake.

  • Exposure to machine learning pipelines or real-time streaming data systems.

  • Knowledge of data governance frameworks and data security compliance.

  • Background in finance, telecom, or enterprise-scale environments.

Education

  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.

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