What are the responsibilities and job description for the Senior Data Engineer position at Charles Schwab Inc.?
Your Opportunity
At Schwab, you are empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us “challenge the status quo” and transform the finance industry together.
Would you like to be part of a new team chartered to build the next generation data & analytics platform supporting Customer Analytics? The Client Data Technology (CDT) team is responsible for Charles Schwab’s client data platform that drives differentiated experiences for customers, accounts, households, and advisors through various channels (Schwab.com, call centers, branches, etc).
We are looking for a Senior Data Engineer to develop and enable the strategic use of customer focused, analytical data assets on Google Cloud. Our ideal candidate is enthusiastic about learning new and existing technologies to deliver outstanding data solutions. You need to have proven critical thinking skills and a laser focus on pragmatic problem solving. We require strong ethics, analytical thinking, and the ability to partner with, and influence business stakeholders and technologists across the organization. You should have backgrounds in both software engineering and data engineering, along with a strong passion for data integration technology.
What you have
Required Qualifications
- 8 years designing, developing, and supporting analytical solutions using modern data warehouse solutions such as BigQuery (preferred), Snowflake, or Redshift
- 8 years designing and developing object-oriented components and frameworks using Java or Python
- 8 years working on agile teams delivering data solutions on time with high quality
- 5 years designing, developing, and supporting real-time data pipelines and streaming analytics using modern data integration tools such as GCP Composer & Dataflow or Apache Airflow & Beam
- 5 years translating business requirements into resilient solution designs
- 5 years prioritizing and planning development work, identifying dependencies, breaking down user stories, and writing efficient, intuitive technical documentation
- 5 years building relationships with domains and teams across large organizations
- 3 years designing and coordinating complex development projects spanning multiple departments
- 3 years writing automated unit tests for data interfaces & data pipelines
- 3 years coaching engineers, fostering a culture of excellence, and challenging the status quo
- 3 years defining and driving data quality and metadata management strategies
- 3 years identifying opportunities for continuous improvement and advocating for their prioritization
Preferred Qualifications
- Solid understanding of customer analytics, how analytical data assets are designed to support maximum business value, and delivering optimal solutions based on business context
- Ability to translate relational and non-relational data into dimensional data models
- Exceptional critical thinking skills and insatiable intellectual curiosity
- Demonstrated ability to quickly investigate and comprehending new data technologies
- Outstanding interpersonal skills, including teamwork, communication, and negotiation, cultivating a culture of open feedback and promoting accountability across the team
