Senior Data Engineer

Collaborate with ML and full-stack teams on document mining challenges

Scale data pipelines efficiently

Build and maintain dashboards in Amazon QuickSight.

Manage datasets and data sources effectively.

Lead the development of data strategies.

Oversee cross-functional data product initiatives.

Lead installation and setup of Fivetran products.

Configure data replication connectors via multiple interfaces.

Own the Salesforce platform roadmap.

Align multiple departments with a unified Salesforce stack.

Drive AI compliance and governance strategy.

Manage AI training data controls for privacy and performance.

Design and maintain marketing analytics data models.

Collaborate with cross-functional teams to define data needs.

Manage external operations vendors.

Lead employee communications.

Drive AI programs across internal and customer domains.

Partner with AI Engineering for scalable programs.

Lead the design of AI-ready data architecture.

Mentor engineers and improve data platform standards.

Design systems for product telemetry and analytics.

Ensure data reliability and scalability.

Optimize the revenue tech stack.

Lead CRM workflow design and integrations.

Define and ship integrations for external knowledge sources.

Collaborate with teams to enhance data retrieval and indexing.

Define long-term strategy for health data platform.

Collaborate on data ingestion and processing.

Build backend systems for enterprise controls.

Design region-aware architectures for compliance.

Develop a long-term data strategy.

Build a scalable data engine for marketplace.

Lead the analytics engineering team to scale the data warehouse.

Mentor and provide feedback to junior engineers.

Define a long-term strategy for a unified health data platform.

Architect ingestion and processing of large-scale health data.

Lead the Data Experience for a no-code AI-first platform.

Bridge customer needs with product strategy and data architecture.

Build and manage data pipelines.

Transform telemetry into datasets.

Build and manage data pipelines.

Collaborate with data scientists for model development.

Lead cross-functional initiatives using GenAI.

Prototype AI-assisted decision-making tools.

Define and execute data infrastructure strategy.

Align data priorities across multiple departments.

Lead complex deals and align teams for business proposals.

Represent customer needs in product development.

Assist with account-based marketing initiatives.

Ensure effective planning and logistics for field marketing.

Architect and deliver enterprise Airtable implementations.

Lead the design of AI solutions during professional services.

Define and execute AI product strategy.

Prioritize AI use cases across IT functions.

Design and implement AI control plane.

Build autonomous agents for engineering tasks.

Develop product strategy for data solutions.

Transform manual reporting to self-serve products.

Own and drive technical programs from concept to launch.

Align stakeholders and identify risks and dependencies.

Define product vision and roadmap for Data Agent.

Own the end-to-end product lifecycle from discovery to launch.

Lead data transformation and analytics projects.

Automate workflows and reporting processes.

Define and manage privacy program roadmaps.

Implement privacy requirements across multiple teams.

Capture business logic for modeling.

Define standards for dimensional modeling.

Design and deploy automation for compensation processes.

Lead system integrations with HRIS and compensation software.

Own the strategy and execution of data services.

Define the multi-year vision for data services.

Manage Salesforce user permissions and configurations.

Optimize Salesforce Flows and validation rules.

Architect and maintain the People data platform.

Integrate Workday and People tools into scalable pipelines.

Architect and deliver a unified Data Cloud platform.

Lead AI-native capabilities including RAG and embeddings.

Translate behavioral data into insights.

Lead reporting discussions with stakeholders.

Lead end-to-end data architecture implementation.

Enhance data modeling and performance optimization.

Define product vision and strategy.

Analyze link activity data metrics.

Design modern data architectures.

Lead technical presales initiatives.

Lead the development of data strategies.

Oversee cross-functional data product initiatives.

Partner with leadership for data-driven decision making.

Build ETL/ELT pipelines for HR data.

Own the roadmap for data products.

Collaborate with teams to scale data assets.

Align go-to-market goals across multiple departments.

Establish and manage unified KPIs and SLAs.

Design and implement enterprise data architectures.

Lead data modeling and governance initiatives.

Lead the analytics engineering team.

Develop a robust analytics platform.

Drive AI activation across the organization.

Establish and scale an AI Champions Network.