Senior Data Engineer, Data Warehouse Lead (GCP)

The Museum of Modern Art

New York (NY)

On-site

USD 140,000 - 160,000

Full time

14 days+
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Job summary

The Museum of Modern Art in New York seeks an experienced Senior Data Engineer to be the technical owner of our data engineering team and primary liaison for departments and analysts relying on our data warehouse. You will guide standards, mentor engineers, and ensure the warehouse meets needs while building scalable ELT pipelines.

Expertise in GCP (BigQuery, Dataflow), SQL, Python, and data modeling is required.

Qualifications

  • Bachelor's or Master's degree in Computer Science or a related field.
  • Minimum of four years of experience as a Data Engineer with data warehousing concepts and best practices.
  • Ability to guide and mentor other engineers and influence technical direction.
  • Proven experience partnering with analysts and stakeholders to understand their needs and translate them into data solutions.
  • Strong data modeling skills and the ability to explain how data relates and how it should be used.
  • Hands-on experience with GCP cloud services, including BigQuery, Cloud Storage, and Dataflow.
  • Proficiency in SQL and experience with database management systems such as MS SQL Server and PostgreSQL.
  • Experience building and maintaining ETL pipelines using tools like Apache Airflow or Google Cloud Composer.
  • Proficiency with Python and pandas.
  • Experience with other programming languages and paradigms such as C#, nodeJS and Ruby.
  • Knowledge of managing Linux and Windows servers.
  • Experience with data modeling and data visualization tools.
  • Experience with software development methodologies such as Agile.
  • Familiarity with version control systems like Git.
  • Excellent problem-solving and analytical skills.
  • Strong communication and collaboration skills.

Responsibilities

  • Serves as the technical anchor and mentor for the data engineering team, setting standards, reviewing work, and guiding design and architecture decisions.
  • Owns the relationship with other departments and data analysts, gathers their data needs, and ensures the data warehouse supports them.
  • Acts as the subject-matter expert on our data, advising analysts on data structures, sources, and querying.
  • Designs, develops, and maintains the data warehouse in Google Cloud Platform (GCP), ensuring scalability, performance, and reliability.
  • Builds and manages robust ELT pipelines to extract, transform, and load data from various sources into the data warehouse.
  • Defines and maintains data models that make data consistent and easy to understand for analysts and business users.
  • Manages and maintains databases, including MS SQL Server and PostgreSQL, ensuring data integrity and security.
  • Develops and maintains small software applications to support data management tasks and improve operational efficiency.
  • Collaborates with stakeholders to gather data requirements and translate them into technical solutions.
  • Troubleshoots data-related issues and provides timely solutions to ensure data availability and accuracy.
  • Stays up-to-date with the latest data engineering technologies and best practices, and shares them with the team.
  • Performs any other duties reasonably related to the functions described above.

Skills

Data warehousing concepts
Mentoring & leadership
Stakeholder collaboration
SQL proficiency
Python
Pandas
Problem-solving
Communication skills
Agile

Education

Bachelor's or Master's degree in Computer Science or related field

Tools

Google Cloud Platform (GCP)
BigQuery
Dataflow
Cloud Composer
Apache Airflow
MS SQL Server
PostgreSQL

Job description

The Museum of Modern Art in New York seeks an experienced Senior Data Engineer to be the technical owner of our data engineering team and primary liaison for departments and analysts relying on our data warehouse. You will guide standards, mentor engineers, and ensure the warehouse meets needs while building scalable ELT pipelines.

Expertise in GCP (BigQuery, Dataflow), SQL, Python, and data modeling is required.

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