Data Engineer

Data Engineer

Department: Data

Employment Type: Full Time

Location: Remote

Description

Grasshopper Bank is a client-first, digital bank built for the business and innovation economy, with an obsession for providing leading-edge technology, solutions-driven products and superior service through a combination of passionate people and digital resources.
We are a highly experienced team who pride ourselves on diversity of thought and perspective.  Nationally chartered, our portfolio of products and services range from VC, PE & Portfolio Companies to SBA Lending, as well as direct SMB and Embedded Banking.
Our entrepreneurial drive allows us to support the growth and success of a wide range of clients at every stage of their business through inclusive partnership.  We seek out team members who will enable both our organization and our people to grow and thrive through collaboration and acting with integrity and respect.
Our focus on cross-functional teamwork provides a culture where ideas are valued, accountability is encouraged, and successes are celebrated. We welcome all those searching for the opportunity to contribute to banking innovation that influences and supports the emerging digital world of Financial Services.
Our digital first approach enables our teams the flexibility to work remotely. We have offices in NYC and Boston.

What you'll do:

Reporting to our Principal Data Architect, you will be instrumental in designing, building, and maintaining our data infrastructure and pipelines on our cloud platform. You will work closely with data scientists, analysts, and other engineers to enable data-driven decision-making across the organization. If you are a problem-solver with a strong understanding of data lakes, data warehousing, ELT/ETL processes, and the Cloud ecosystem such as GCP, AWS or Azure, we encourage you to apply
Responsibilities include:

• Design, develop, and maintain scalable and efficient data pipelines using various cloud platform services (e.g., BigQuery, Dataflow, Cloud Functions, Pub/Sub, Cloud Composer).
• Build and optimize data models and data lake solutions in BigQuery.
• Implement and manage ELL/ETL processes to ingest, transform, and load data from diverse sources into our data warehouse.
• Ensure data quality, integrity, and reliability through monitoring, testing, and validation processes.
• Collaborate with data scientists and analysts to understand their data needs and provide them with clean and accessible data.
• Develop and maintain data operations policies and procedures.
• Implement and manage data security and access controls.
• Monitor and optimize the performance and cost-effectiveness of our data infrastructure.
• Stay up-to-date with the latest data technologies and best practices.
• Troubleshoot and resolve data-related issues in a timely manner.
• Document data pipelines, data models, and infrastructure designs.
• Participate in code reviews and contribute to the team's knowledge sharing

What you need:

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field.
• 1 to 3 years of experience in data engineering or a similar role.
• Proven experience designing, building, and deploying data solutions on Cloud Platform such as GCP, AWS or Azure.
• Strong proficiency in SQL and experience working with large datasets and data warehousing concepts (e.g., schema design, partitioning, clustering).
• Experience with ELT/ETL tools and frameworks (e.g., Apache Beam, Dataflow, Cloud Composer).
• Familiarity with at least one programming language such as Python, Java, or Scala.
• Understanding of data governance, data quality, and data security principles.
• Experience with version control systems (e.g., Git).
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills

Nice to haves:

• Google Cloud certifications (e.g., Professional Data Engineer)
• Experience with real-time data processing using GCP services like Pub/Sub and Dataflow
• Familiarity with Infrastructure-as-Code (IaC) tools like Terraform or Deployment Manager
• Experience with data visualization tools (e.g., Looker, Tableau)
• Exposure to machine learning workflows and data pipelines on GCP
• Experience with DevOps practices and CI/CD pipelines for data infrastructure
• Experience working in an Agile development environment