Data Science & Research Engineer Signal1 Integration (Contract)

Data Science & Research Engineer - ML Ops & Research Integration (Contract) 8 months Remote Senior BI/analytics engineering role responsible for building and enhancing Signal1 integration data products and analytics assets. The role blends a Senior BI Developer profile with modern tooling—developing governed DBT models and curated marts on Databricks and delivering Power BI semantic models and dashboards. Work is focused on development- stage build and initial validation for controlled deployment.

Key Responsibilities:

Design and implement net-new or significantly enhanced DBT models, curated data marts, and governed tables/views supporting Signal1 onboarding and enterprise analytics consumption. Design and implement net-new or significantly enhanced DBT models, curated data marts, and governed tables/views supporting Signal1 onboarding and enterprise analytics consumption. Develop transformations and data products on Databricks (notebooks/jobs, Delta patterns) as part of defined build scope. Build Power BI datasets/semantic models and dashboards tied to approved deliverables; implement refresh, row-level security, and performance best practices. Partner directly with Signal1 to align candidate models for ingestion (inputs/outputs, metadata, versioning, and governance requirements). Configure and validate Signal1 monitoring for onboarded models (monitor definitions, thresholds, alerting hooks, and initial baselines); support initial monitoring sign-off. Define and validate business metrics and reconciliation checks; retain initial testing evidence and sign-off for releases. Author data contracts, lineage, and documentation (definitions, ownership, SLAs) required for governed deployment and reuse. Build Power BI datasets/semantic models and dashboards tied to approved deliverables; implement refresh, row-level security, and performance best practices. Define and validate business metrics and reconciliation checks; retain initial testing evidence and sign-off for releases. Author data contracts, lineage, and documentation (definitions, ownership, SLAs) required for governed deployment and reuse. Partner with Data Science, Product, and platform owners to align data products to downstream monitoring, governance, and stakeholder needs. Develop and validate SQL-based performance metrics and supporting logic as part of initial delivery and acceptance testing. Create data contracts and documentation (lineage notes, definitions, quality checks) required for governed deployment. Partner with Data Science and platform owners to integrate ingestion assets with downstream monitoring/governance workflows. Support initial release readiness by producing validation queries and evidence that ingestion outputs meet requirements.

Required Qualifications:

5 years of experience as a BI Developer / Analytics Engineer / Data Engineer delivering production reporting and curated datasets. Advanced SQL skills (complex transformations, performance tuning, reconciliation). Hands-on experience with DBT (models, tests, documentation) and building governed transformation layers. Hands-on experience building in Databricks (notebooks/jobs; Lakehouse concepts such as Delta). Hands-on experience with Power BI (semantic models/datasets, DAX fundamentals, dashboard development, refresh and security patterns). Experience with version control and code review practices; ability to produce clear technical documentation. Hands-on experience with DBT (models, tests, documentation) and modern data warehouse concepts. Strong SQL skills; ability to create reusable, well-documented transformation logic. Experience with version control and code review practices.

Preferred Qualifications:

Experience defining metric layers/semantic models and governed KPI catalogs. Experience supporting AI/ML data products (feature stores, model monitoring inputs) or analytics governance programs. Familiarity with data quality frameworks and operationalizing acceptance criteria. Python experience for data tooling/automation. Experience defining data quality checks and operationalizing acceptance criteria. Familiarity with Python for data tooling/automation. Deliverables /

Success Measures:

Deployed DBT models and curated marts on Databricks for defined onboarding scope; Power BI semantic models/dashboards delivered with documentation and security patterns; documented data contracts/lineage; initial validation evidence for releases; reduced onboarding backlog for Signal1 integrations. $TB_PH #ZRHC #Linkd #Linkd Why TalentBurst? At TalentBurst, we deliver more than talent, we deliver outcomes. We partner with you to move quickly and connect you to opportunities aligned with your skills and long term growth. Backed by precision, transparency, and results, we connect top talent with leading organizations through trusted partnerships. We offer competitive compensation and comprehensive benefits, including medical, dental, vision, and retirement options. TalentBurst is an equal opportunity employer committed to an inclusive and diverse workforce.