Job Description

Title: Data Engineering Lead

Location: Pittsburgh, PA (3 days' on-site/hybrid)

Rate: Only W2

Duration: initially through end of 2025 – likely extended in 2026 (potential for conversion)

we have an immediate opening for a Data Engineering Lead. This is a very hands-on Technical Lead role – will be doing 75-80% hands-on Data Engineering including design.

The ideal candidate is an experienced Data Engineering Lead with a strong background in Snowflake, Python, PySpark, SQL, and Azure cloud-based data solutions. They are a self-motivated, independent problem-solver who is eager to learn new skills and adapt to changing technologies. Collaboration, performance optimization, and a commitment to maintaining data security and compliance are critical for success in this role.

Day-to-Day

• Serve as the subject matter expert in technologies used for our data strategy in the cloud.
• Design, develop, optimize, and maintain data architecture and pipelines that adhere to ETL principles and business goals.
• Solve complex data problems to deliver insights that helps the organization's business to achieve their goals.
• Create data products for analytics and data scientist team members to improve their productivity.
• Advise, consult, mentor and coach other data and analytic professionals on data standards and practices.
• Foster a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions.
• Lead the evaluation, implementation and deployment of emerging tools and process for analytic data engineering to improve the organization's productivity as a team.
• Partner with business analysts and solutions architects to develop technical architectures for strategic enterprise projects and initiatives.
• Utilize programming & scripting languages like Python, Spark (PySpark) and Open-Source RDBMS and NoSQL databases and Cloud based data warehousing services such as and Snowflake
• Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community

Primary Skill Set:

• Bachelor's degree in computer science engineering or a related discipline, or equivalent work experience required.
• 7-10 years of experience in data management services such as the following required.
  • Data Handling: Managing, storing, and organizing large volumes of data.
  • Data Integration: Combining data from different sources to create a unified view.
  • Data Quality: Ensuring the accuracy, consistency, and reliability of data.
  • Data Security: Protecting data from unauthorized access and breaches.
  • Data Analysis: Analyzing data to extract meaningful insights and support decision-making.
  • Database Management: Working with various database systems to store and retrieve data efficiently.
  • Big Data Technologies: Utilizing tools and technologies like Hadoop, Spark, and others to process and analyze large datasets.

• 5+ years of advanced Python programming experience is required.
• 5+ years of advanced SQL querying skill is required.
• 2+ years of Big Data technologies like HDFS , Spark (PySpark) and various data store technologies from on-prem to cloud required.
• 2+ years of Azure Cloud experience required.
• 2+ years' experience with enterprise BI Reporting Tools such as PowerBI, Tableau or Qlikview (PowerBI preferred).
• 1-2 years of Snowflake Cloud Database required.
• Experience in creating data pipelines to move and transform data on a large scale in an enterprise organization.
• Strong experience in SDLC, DevOps processes – CI/CD tools, Git, etc.
• Strong analytical skills and attention to detail 
• Improve data quality and performance.

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