Sr Specialist - Software Development & Engineering

Your Opportunity

Schwab remains committed to providing increased visibility to career growth opportunities and job requirements. This posting announcement is part of increased transparency and while all qualified applicants will be reviewed and considered, this organization has a preferred candidate identified for this role. 

At Schwab, you’re 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. 

We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location(s).

At Schwab, the Data and Rep Technology (DaRT) organization governs the strategy and implementation of the enterprise data warehouse, Data Lake, and emerging data platforms. Our mission is to drive activation of data solutions, rep engagement technology (Sales, Marketing and Service) and client intelligence to achieve targeted business outcomes, address data risk and safeguard competitive edge. We help Marketing, Finance, Risk and executive leadership make fact-based decisions by integrating and analyzing data.   

As part of the Business Data Delivery team, you will partner with business stakeholders, data engineering teams, architects, product owners, and cross-functional technology partners to design, develop, and deliver scalable data solutions for analytics, reporting, operational insights, and data science use cases. Our team uses modern data engineering platforms and tools including Informatica Intelligent Cloud Services (IICS), Google Cloud Platform (GCP), BigQuery, SQL, Python, and enterprise scheduling/orchestration capabilities. In this role, you will design, develop, test, implement, and support enterprise data integration solutions with a focus on quality, automation, data governance, production stability, and measurable business value. 

In this role you will be:

• Designing, developing, testing, and implementing scalable data ingestion and transformation workflows using IICS, BigQuery, SQL, Python, and modern data engineering techniques 
• Developing data pipelines across a wide variety of data sources and ingestion patterns, including batch, near real-time, and event-driven processing 
• Leading small to moderately complex data engineering deliverables from requirements through design, development, testing, implementation, and production support 
• Working with business analysts, product owners, data modelers, architects, and stakeholders to understand business requirements, data requirements, source-to-target logic, and use cases 
• Creating and maintaining technical documentation, including mapping specifications, data lineage, transformation rules, data quality requirements, operational support notes, and implementation details 
• Partnering with technical directors, data modelers, and cross-functional teams to ensure accurate, efficient, standards-aligned implementation of data solutions 
• Defining and executing quality assurance, data validation, reconciliation, and regression testing processes to reduce production issues 
• Building reusable Python scripts and utilities to automate validation, file processing, reconciliation, monitoring, and operational support activities 
• Providing technical guidance to onshore and offshore development teams and supporting design/code reviews 
• Reviewing data engineering deliverables from third-party vendor teams to ensure quality, maintainability, and alignment with enterprise standards 
• Advocating for Agile delivery practices, effective estimation, dependency management, and transparent communication of risks, blockers, and status 
• Ensuring consistency with published development, coding, testing, release management, data governance, and production support standards 

What you have

To ensure that we have fulfilled our promise of "challenging the status quo," this role has specific qualifications that successful candidates should have.

Required:

• Demonstrated experience as a Data Engineer or ETL/ELT Developer with a track record of delivering high-quality, production-ready data solutions with minimal defects 
• 3-5 years of hands-on experience designing and developing data integration pipelines using Informatica Intelligent Cloud Services (IICS), Informatica PowerCenter, or similar integration platforms 
• 3-5 years of experience working with cloud and data warehouse platforms, preferably Google Cloud Platform (GCP), BigQuery, Teradata, or comparable enterprise data platforms 
• Strong hands-on experience with SQL, including developing, tuning, debugging, and optimizing complex queries, data transformations, and analytical workloads 
• Hands-on experience with Python for data engineering automation, validation, reconciliation, file processing, monitoring, and operational utilities 
• Experience with batch, near real-time, and/or real-time data ingestion patterns and the ability to select appropriate design patterns based on business and technical needs 
• Experience implementing data quality checks, exception handling, reconciliation, audit controls, and validation rules 
• Experience with BigQuery concepts such as partitioning, clustering, performance optimization, cost-conscious query design, and scalable data modeling practices is highly desirable 
• Experience creating and maintaining source-to-target mappings, transformation logic, data lineage, operational runbooks, and support documentation 
• Experience with scheduling and orchestration tools such as Control-M, ESP, or similar platforms 
• Prior experience partnering with vendors, offshore development teams, internal technology teams, business stakeholders, architects, and product owners 
• Ability to quickly learn new technologies and apply them to improve delivery quality, automation, scalability, and operational efficiency 
• Strong analytical, problem-solving, influencing, prioritization, decision-making, ownership, and conflict resolution skills 
• Exceptional interpersonal skills, including teamwork, written and verbal communication, stakeholder management, and negotiation

Preferred:

• Experience working in large-scale enterprise environments involving RDBMS, EDW, NoSQL, Big Data, cloud data platforms, or hybrid data ecosystems is preferred 

In addition to the salary range, this role is also eligible for bonus or incentive opportunities