Data Engineer

  • Pittsburgh, PA
  • Posted 26 days ago | Updated 3 days ago

Overview

Hybrid
$100,000 - $130,000
Full Time
Accepts corp to corp applications
10% Travel

Skills

Amazon Web Services
Apache Hive
Apache Hadoop
Apache Spark
Continuous Delivery
Continuous Integration
Data Governance
Extract
Transform
Load
Good Clinical Practice
Workflow
Version Control
ELT
Git
SQL
Streaming
Microsoft Azure
Big Data
PySpark
Python
HDFS
Finance

Job Details

Location: Pittsburgh, Cleveland, or Dallas (Hybrid: 3 days onsite)
Type: Contract-to-Hire at large (top 15) financial institution.
Sponsorship is not available for this position.

Experience: 4-6 years
Conversion Salary Range: $100K $130K Join a growing data organization at the forefront of innovation in financial services. We re seeking talented data engineers to help modernize and scale data capabilities across multiple lines of business, including commercial, retail, and wealth. You ll work on high-impact projects that span both on-prem and cloud environments, supporting next-generation data pipelines, governance, and analytics. If you re passionate about building, optimizing, and delivering trusted data at scale, we want to hear from you.

Key Responsibilities:

  • Proficiency in Python and PySpark Essential for building and optimizing data pipelines for large-scale datasets.
  • Experience with Distributed Computing Environments
  • Familiarity with Bigdata, Hadoop, Hive, and HDFS formats is critical.
  • Strong Communication Skills
  • The role involves collaboration with cross-functional teams, making clear and effective communication important, Background in Data Modeling and ETL Development Design and implement scalable data pipelines using Hadoop, Spark, and Hive.
  • Build and maintain ETL/ELT frameworks for batch and streaming data
  • Collaborate with product teams to ingest, transform, and serve model-ready datasets
  • Optimize data workflows for performance and reliability
  • Ensure pipeline quality through validation, logging, and exception handling

Preferred Skills:

  • Hadoop, Hive, Spark, SQL, Python
  • Experience with version control (Git) and CI/CD tools
  • Familiarity with modern data governance and observability practices
  • Cloud experience a plus (AWS, Azure, Google Cloud 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.

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