Data Engineer / Data Scientist (Hybrid)

VACO LLC
Pittsburgh, United States of America
12 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate

Job location

Pittsburgh, United States of America

Tech stack

Agile Methodologies
Airflow
Amazon Web Services (AWS)
Data analysis
Azure
Big Data
Google BigQuery
Computer Programming
Data Architecture
Information Engineering
ETL
Data Visualization
Data Warehousing
Python
Machine Learning
Scrum
Power BI
TensorFlow
Standard Sql
Tableau
PyTorch
Snowflake
Spark
Containerization
Scikit Learn
Kubernetes
Information Technology
Data Analytics
Machine Learning Operations
Data Pipelines
Docker
Redshift

Job description

  • Design, build, and maintain scalable data pipelines and ETL/ELT workflows to support analytics and machine learning initiatives
  • Develop and optimize data architectures in cloud and on-prem environments (e.g., AWS, Azure, or GCP)
  • Analyze large, complex datasets to extract insights and support business strategy
  • Build, train, and deploy machine learning models for forecasting, classification, and optimization use cases
  • Collaborate with cross-functional teams including product, engineering, and business stakeholders to translate data needs into technical solutions
  • Ensure data quality, integrity, and governance across systems
  • Create dashboards, visualizations, and reports using tools like Power BI, Tableau, or similar
  • Continuously improve data processes and recommend new tools, technologies, and methodologies

Requirements

We are seeking a versatile Data Engineer / Data Scientist to join a growing, data-driven organization just north of downtown Pittsburgh. This hybrid role blends data engineering, analytics, and machine learning, offering the opportunity to work across the full data lifecycle-from building scalable data pipelines to developing predictive models that drive business decisions., * Bachelor's degree in Computer Science, Data Science, Engineering, or related field (Master's preferred)

  • 3+ years of experience in data engineering, data science, or a hybrid role
  • Strong programming skills in Python and SQL
  • Experience building data pipelines and working with large datasets (e.g., Spark, Airflow, or similar tools)
  • Hands-on experience with cloud platforms (AWS, Azure, or GCP)
  • Familiarity with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch)
  • Experience with data visualization and BI tools
  • Strong problem-solving skills and ability to communicate technical concepts to non-technical stakeholders, * Experience with containerization and orchestration tools (Docker, Kubernetes)
  • Knowledge of data warehousing solutions (Snowflake, Redshift, BigQuery)
  • Familiarity with MLOps practices and model deployment pipelines
  • Experience in Agile or Scrum environments

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