Job DescriptionThe Sr System Analyst, Data Activation Engineer, Enterprise Data & Analytics is responsible for building the data integration pipelines and data contracts that connect our target analytics platforms (primarily Google Cloud Platform, other supported platforms are C3.ai, and Azure Databricks) to source systems and middleware. The role owns the functional and technical design of these interfaces, including identifying required tables and columns, validating data sensitivity and handling requirements, and selecting the right integration methodology based on platform capabilities. Data integrity is a core deliverable, not an afterthought, and the engineer is accountable for it across every stage of the pipeline.
This is a collaborative role. The engineer partners closely with solution engineers, source system owners, and business subject matter experts to confirm data needs and shape use case delivery. They also design and implement the monitoring and observability layers on each interface, making sure data arrives intact, complete, and on time end to end. Success in this role means dependable pipelines, clear contracts between systems, and analytics consumers who can trust the data theyre working with.
This position does not provide employment pursuant to the terms of a STEM OPT Training Plan.
ResponsibilitiesCore Responsibilities- Design and build data integration pipelines that move data reliably from source systems and middleware into the target analytics platform (primarily Google Cloud Platform; other platforms are Azure Databricks & C3.ai)
- Define and maintain data contracts that set clear expectations for schema, frequency, quality, and ownership between producers and consumers
- Produce functional and technical interface designs, including source-to-target mappings, transformation logic, and field-level specifications
- Evaluate data sensitivity and classification requirements, applying the right controls for protected, confidential, or regulated data
- Select integration patterns and methodologies (batch, streaming, API-based, CDC, etc.) that fit the use case and align with supported platform capabilities
- Partner with solution engineers, source system owners, and business SMEs to translate use case requirements into concrete data delivery plans
- Validate data integrity end to end through reconciliation checks, row counts, checksums, and other verification techniques
- Build monitoring and observability into every interface, with alerting on freshness, completeness, schema drift, and failure conditions
- Troubleshoot pipeline issues and lead root cause analysis when data arrives late, incomplete, or malformed
- Document interfaces, lineage, and operational runbooks so that pipelines remain supportable and auditable over time
QualificationsRequired Education/Experience- Master's Degree in Computer Science, Engineering, Math, Business, or technology-centric field and a minimum of 2 years relevant full time work experience or
- Bachelor's Degree in Computer Science, Engineering, Math, Business, or technology-centric field and a minimum of 3 years relevant full-time work experience
Relevant Work Experience- Hands-on experience designing and building data integration pipelines across batch, streaming, API, and change data capture patterns, with one or more of: Azure Data Factory, SSIS, Google Cloud data integration services (Dataflow, Dataform, Data Transfer Service, gcloud CLI), or comparable tooling, required
- Strong background in source to target mapping, schema design, and writing technical specifications that engineers and analysts can both work from, required
- Working knowledge of modern data platforms and integration tooling, with the judgment to match the right pattern to the right use case, required
- Track record of partnering across solution engineers, source system owners, and business SMEs to turn fuzzy requirements into reliable, production-grade data delivery, required
- Practical understanding of data sensitivity, classification, and handling requirements, including how to apply controls for protected or regulated data, preferred
- Experience defining and operationalizing data contracts, including schema versioning, ownership boundaries, and quality expectations between teams, preferred
- Proven ability to implement monitoring and observability on data pipelines, covering freshness, completeness, schema drift, and failure alerting, preferred
Skills and Abilities- Strong written and verbal communication skills
- Possesses flexibility to work in a fast paced, dynamic environment
- Ability to work within tight timeframes and meet strict deadlines
- Demonstrated problem solving skills
- Effective interpersonal skills
- Ability to drive multiple projects to successful completion
- Demonstrated time management and priority setting skills
- Ability to drive multiple projects to successful completion
- Well organized, detail oriented and flexible to handle multiple assignments
Licenses and Certifications- Driver's License Required
- Other: Technical certification(s) in IT Preferred
- Other: Google Professional Data Engineer Preferred
- Other: Google Associate Data Practitioner Preferred
- Other: Databricks Associate Data Engineer Preferred
- Other: Databricks Professional Data Engineer Preferred
Physical Demands- Sit or stand to use a keyboard, mouse, and computer for the duration of the workday
Additional Physical Demands- The selected candidate will be assigned a System Emergency Assignment (i.e., an emergency response role) and will be expected to work non-business hours during emergencies, which may include nights, weekends, and holidays.
- Available to work off hours as operationally required
