Overview
Hybrid
Depends on Experience
Full Time
Accepts corp to corp applications
No Travel Required
Unable to Provide Sponsorship
Skills
Analytics
Amazon Redshift
Apache Hive
Amazon Web Services
Analytical Skill
Apache Hadoop
Apache Kafka
Apache Spark
Application Development
Business Intelligence
Cloud Computing
Data Storage
Data Warehouse
Data Management
Data Processing
Data Quality
Collaboration
Data Engineering
Data Governance
MapReduce
Electronic Health Record (EHR)
Management
NoSQL
SQL
Snow Flake Schema
PySpark
Databricks
ELT
Job Details
Job Title: Data Engineer
Client: Capital One
Location: Richmond, VA (Primary) / McLean, VA (Secondary) / Plano, TX (Tertiary) (Hybrid)
Duration: 12+ Months with possible of extension
Job Overview:
We are seeking an experienced Data Engineer to join a project team responsible for designing, building, and optimizing data pipelines and data storage solutions that support enterprise analytics and business intelligence initiatives. The ideal consultant will have hands-on experience with modern data engineering tools, distributed systems, cloud platforms (AWS), and large-scale ETL/ELT data processing.
Required Skill:
- 4+ years of experience in application development using Python, PySpark, SQL, etc.
- 4+ years of experience working with public cloud platforms – AWS preferred.
- 2+ years of experience with distributed data/computing tools (e.g., MapReduce, Hadoop, Hive, EMR, Kafka, Spark).
- 4+ years of hands-on experience in data warehousing (e.g., Redshift, Snowflake).
- 2+ years of experience implementing NoSQL
databases. - 2+ years of experience working with Databricks.
Job Description:
- Design, construct, install, test, and maintain robust and scalable data management systems.
- Build high-performance data pipelines for ingestion, transformation, and loading using Python, PySpark, SQL, and cloud-native services.
- Develop and manage modern data warehouse solutions (e.g., Amazon Redshift, Snowflake) ensuring data accuracy, scalability, and reliability.
- Collaborate closely with Data Scientists, Analysts, Engineers, and business stakeholders to understand data requirements and deliver optimized solutions.
- Implement automated monitoring, alerting, and validation for data pipelines to ensure stability and data quality.
- Optimize data retrieval, processing, and consumption for a wide range of analytical use cases.
- Ensure compliance with data governance, security, and privacy practices across the data lifecycle.
- Evaluate new tools, frameworks, and best practices to continuously improve the organization’s data platform.
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.