Lead the design and operation of scalable batch and streaming data pipelines and trusted data context layers for Cisco’s Network Platform, ensuring data quality, observability, and AI readiness across structured and unstructured data.
Locations (5)
San Jose, California, United States
New York City, New York, United States
Washington, United States
Illinois, United States
Canada
Compensation
The starting salary range posted for this position is $167,700.00 to $245,200.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits.
Responsibilities
Set technical direction for reliable, scalable batch and streaming pipelines and data products
Define and continuously improve data quality, freshness, availability, observability, recovery, and cost expectations
Lead production incident investigations to deliver lasting fixes
Build and evolve a trusted, machine‑readable data context layer integrated with catalog/governance systems
Apply AI and agentic workflows to scoped data engineering needs
Requirements
Bachelor's degree
Master's degree
PhD
Nice to have: building trusted data context layers
Senior BI Analyst responsible for owning and maintaining HelloFresh’s data landscape, building ETL pipelines, data models, and executive dashboards to support decision‑making across the organization.
Compensation
$82,000—$92,000 CAD
Responsibilities
Design, develop, and maintain ETL/ELT pipelines using dbt, Databricks, Spark SQL, and Airflow
Implement automated data quality checks, monitoring, and alerting
Write performant SQL for large‑scale data transformations
Build and maintain executive‑level BI dashboards (Tableau, Databricks)
Own critical business reporting (WBRs, QBRs, forecasting)
Senior BI Analyst responsible for owning and maintaining HelloFresh’s data landscape, building ETL pipelines, data models, and executive dashboards to support decision‑making across the organization.
Compensation
$82,000—$92,000 CAD
Responsibilities
Design, develop, and maintain ETL/ELT pipelines using dbt, Databricks, Spark SQL, and Airflow
Act as steward of domain data landscape implementing automated quality checks and monitoring
Write performant SQL for large‑scale data transformations
Build and maintain executive‑level BI dashboards (Tableau, Databricks)
Own critical business reporting and act as analytics partner across Product, Marketing, Finance, and Operations
Build and maintain the data platform behind Kindsight's customer-facing analytics products, ingesting data from customer Salesforce environments into an AWS data lake and transforming it through a dimensional data warehouse that powers dashboards and AI-driven insights.
Build and maintain ELT pipelines that ingest data from customer Salesforce environments into our AWS data lake, covering both scheduled batch loads and near-real-time change data capture.
Develop data transformation layers (medallion architecture) and dimensional models in dbt on Redshift or Snowflake, implementing incremental logic, slowly changing dimensions, and derived metrics against defined specifications.
Write and optimize advanced SQL for transformation, aggregation, and data quality validation across large, multi-tenant datasets.
Work hands-on with AWS: S3, Glue, Athena, Redshift, Step Functions, Lambda, IAM, Lake Formation, and CloudWatch.
Onboard new customer data sources by extending existing configuration-driven pipelines, and verify each onboarding against defined acceptance criteria.
Requirements
Bachelor's degree in Computer Science, Data Science, Engineering, or a related field, or equivalent practical experience.
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