Sr. Data and Automation Engineer, Enterprise Applications

You will work independently with business stakeholders to transform complex requirements into trusted, governed datasets, reliable integrations, actionable dashboards, and scalable automation. This six-month engagement is focused on delivering documented data products and sustainable solutions that long-term support teams can confidently maintain., * Curated, documented data products supporting use cases such as expense management, learning analytics, gross-to-net reporting, budgeting, and operational reporting.

• Reliable pipelines and integrations connecting enterprise applications and third-party sources to governed datasets.
• Dashboards, metrics, and reporting products for broad General and Administrative (G&A) functions.
• Data quality checks, definitions, documentation, and standards that make enterprise data accessible and trustworthy.
• Automation and integration solutions-or clearly defined roadmaps-to reduce manual data preparation, reconciliation, reporting, and workflow handoffs.
• Handoff documentation and support-ready solutions designed to remain adaptable as enterprise systems evolve., * Lead the design and delivery of curated data products across Databricks, Snowflake, and related platforms.
• Develop ingestion, transformation, data quality, and reusable data modeling solutions.
• Partner with G&A business owners to define analytics requirements, key performance indicators, data definitions, and priority use cases.
• Build pipelines and integrations using APIs, flat files, middleware, Fivetran or similar ingestion tools, and third-party data sources.
• Create dashboards, metrics layers, and insight products for functions including Finance, Human Resources, Procurement, Legal, Compliance, and Commercial Operations.
• Establish standards for data naming, lineage, documentation, access controls, data quality, and long-term support handoff.
• Identify and deliver automation opportunities using Workato, Moveworks, middleware, or similar platforms.
• Evaluate and responsibly apply artificial intelligence tools to simplify processes, improve data stewardship, and accelerate analytics delivery.
• Collaborate with Information Security, Compliance, Legal, and data owners to protect sensitive information and align with privacy, governance, and access requirements.
• Translate ambiguous business needs into clear technical requirements, delivery plans, and measurable outcomes.

• Hands-on experience with:
• Databricks
• Snowflake
• SQL
• Python or PySpark
• Delta Lake
• Fivetran or similar data ingestion tools
• Modern data lakehouse or data warehouse patterns
• Experience designing curated datasets, semantic models, data quality rules, and documentation for business users.
• Experience integrating enterprise data through APIs, flat files, middleware, or integration platform as a service (iPaaS) tools.
• Experience with reporting platforms and reverse extract, transform, load (reverse ETL) or data activation patterns.
• Familiarity with G&A processes and systems, including NetSuite, Coupa, Concur, Workday Adaptive, Ironclad, Emtrain, ComplianceWire, or similar platforms supporting Finance, Procurement, Human Resources, Legal, learning, compliance, or planning functions.
• Experience using Workato, Moveworks, middleware, iPaaS, or comparable automation and integration platforms.
• Ability to convert complex or ambiguous business needs into practical technical requirements and delivery plans.
• Ability to work independently in a fast-paced environment while collaborating with business, technology, compliance, and security partners.

Nice-to-Have Skills

• Experience with ERP platforms beyond NetSuite.
• Experience supporting system migrations or re-pointing integrations and data pipelines as applications change.
• Experience in biotechnology, pharmaceuticals, life sciences, or another regulated environment.
• Experience delivering analytics across multiple G&A functions, including expense management, learning, and workforce metrics.
• Experience with Unity Catalog, Snowflake governance, workflow orchestration, data lineage, data governance, or access management.
• Experience applying artificial intelligence, machine learning, or generative AI to analytics workflows, automation, knowledge retrieval, or operational process improvement., * Bachelor’s degree in Data Engineering, Computer Science, Information Systems, Business Analytics, or a related discipline.
• Equivalent practical experience may be considered.
• At least 5 years of relevant experience in data engineering, analytics engineering, enterprise analytics, business systems, integration, automation, or data product delivery., * Ability to work with sensitive enterprise data in alignment with applicable privacy, governance, security, and access requirements.