Data Engineer (final round in person at NYC)

Data Engineer
Location: New York City, NY (Hybrid)
Employment Type: Contract

Mandatory skills SQL, Python, Google Cloud Platform
Good To Have Tableau, PowerBI & Looker
Job Overview
We are seeking a highly skilled Data Engineer to join our data and analytics team supporting MLB initiatives. The ideal candidate will have strong expertise in SQL, Python, and Google Cloud Platform (Google Cloud Platform), with experience building scalable data pipelines, optimizing data workflows, and enabling data-driven decision-making. This role requires close collaboration with data analysts, business stakeholders, and engineering teams to deliver reliable and high-quality data solutions.

Key Responsibilities
Design, develop, and maintain scalable ETL/ELT pipelines using Python and SQL.
Build and optimize data models, data warehouses, and data lakes within Google Cloud Platform environments.
Develop and maintain data integration solutions across multiple systems and platforms.
Ensure data quality, integrity, governance, and security standards are consistently met.
Monitor, troubleshoot, and optimize data pipeline performance.
Collaborate with analytics and business teams to understand reporting and data requirements.
Create reusable frameworks and automation solutions for data ingestion and transformation.
Support dashboarding and business intelligence initiatives by providing clean, reliable datasets.
Implement best practices for data engineering, code quality, testing, and deployment.
Participate in architecture discussions and contribute to cloud data strategy initiatives.

Required Qualifications
Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
5+ years of experience in Data Engineering or related roles.
Strong hands-on experience with SQL and complex query optimization.
Advanced proficiency in Python for data processing, automation, and pipeline development.
Experience with Google Cloud Platform (Google Cloud Platform) services such as:
BigQuery
Cloud Storage
Dataflow
Dataproc
Cloud Composer
Pub/Sub

Strong understanding of data warehousing concepts and dimensional modeling.
Experience working with large-scale structured and unstructured datasets.
Knowledge of CI/CD processes and version control systems such as Git.