Senior Technical Data Analyst

Location Boston MA or Woodbridge NJ (onsite 4 days a week) - Locals only

Interview Process

1. Video Interview
2. Onsite Interview in Boston MA or Woodbridge NJ

Here is the job description:

Candidates need to understand Data Governance and how it connects different systems.

Informatica experience is MUST. Candidates MUST be technical and understand (Snowflake, Data Lake, SageMaker), the flow of data, and prioritized use cases such as the PLE models. Need to understand both technical and business aspects.

Day to day- candidates would need to prioritize Use Cases: Mary discussed the ongoing prioritization of use cases, with the PLE (policy lifetime expectation) model as an example, requiring data from both Snowflake and SQL Server, and collaboration with business leads to design and enable the use case.

Technical Skills Requirements: Candidates should have experience with cloud offerings, data architecture, and the ability to connect business needs to technical solutions, including understanding metadata capture, cataloging, and the implications for platform design.

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Senior Technical Data Analyst




Transitioning to an AI/ML-driven operating model. The Data Management team within the Data Office will build and deploy an enterprise data governance framework. This framework will ensure data is trusted, secure, compliant, and accessible through Business Intelligence, Machine Learning (ML), and Artificial Intelligence (AI) applications. The team will promote a culture where data is treated as a strategic asset and company resource, with clear accountability for its quality, use and capture.

You will work closely with other Data Office members, IT groups, AI/ML teams, and business partners to drive adoption of enterprise data policies and standards, improve data quality, and reduce data loss/duplication and technical debt on the data platform.

Key Responsibilities

• Support the Data Management leader to design and implement a comprehensive data governance operation aligned to AI/ML-first data strategy, which includes:
  • Informing, influencing, and obtaining buy-in from the entire company on the importance of data governance on business objectives and AI/ML imperative.
  • Developing policies, standards, metrics, tools, and processes to ensure robust and comprehensive documentation of data inventories, meaning, permissions, lineage and quality for downstream enterprise development and application.
  • Driving engagement and adoption with data owners, producers, stewards, AI/ML teams, and stakeholders (such as Legal, Audit/Risk, and Information Security)
• First Priority for the team and you is:
  • Assess usability and completeness of internal catalogs for data on the platform and other sources. Work with relevant business/IT partners to make data governance updates within the catalog and ensure proper ownership, certification, and lifecycle alignment with enterprise standards.
  • Develop and implement metadata and catalog governance standards, including defining tagging frameworks, creating metadata templates, normalizing existing metadata, and establishing validation processes to ensure consistency and quality across reports, dashboards, and other analytics assets.
• Define and enforce promotion and lifecycle governance standards, including establishing processes for assets moving through POC, Development, and Production, implementing governance checkpoints, and documenting approval and ownership requirements aligned to data platform modernization goals.
• Develop and deliver training, enablement, and communication materials to support catalog usage, metadata understanding, and governance adoption, including end-user guidance and stakeholder presentations to promote a data-driven culture.
• Support the Data Management leader to test and integrate a governance tool for the data platform that would complement the governance operating model.
• Help design and support responsible AI usage and controls around data privacy, bias, and regulatory compliance, including working with Advanced Analytics and AI teams to follow/implement them in their use cases.

• Establish and enforce lineage tracking to enable traceability from source systems through downstream consumption.

• Work with IT and business partners to investigate and address data leakage between insurance operations and data stores.
• Collaborate cross-functionally with Data Office, Analytics, and IT teams to ensure consistent adoption of governance practices and support broader enterprise data initiatives.

Qualifications:

• Bachelor's degree in Data Science, Computer Science, Information Systems, Business Administration, or a related field is preferred.
• SQL proficiency

Preferred Experience:

• 5+ years of experience in data governance or enterprise data management, including implementing governance frameworks in complex, multi-system environments.
• Experience supporting AI/ML data requirements, including structured, unstructured, and streaming data.
• Knowledge of MLOps practices, model versioning and deployment pipelines, and AWS services such as Glue, S3, SageMaker, and Snowflake.
• Python programming
• Strong understanding of data privacy, regulatory requirements, and responsible AI practices.
• Demonstrated ability to successfully work in cross-functional environments with business, technology, and analytics teams.
• P&C Insurance experience and working familiarity of insurance underwriting operations and platform systems preferred.