Data Analytics Contractor: 6-9 years (Advanced)

Job-ID29195946Reference26-24663Remote100% Remote The services You will provide the clients project team: As a Data Analytics Contractor, you will analyze and interpret complex data sets to provide actionable insights and support decision-making processes. Collect, process, and analyze large datasets to identify trends, patterns, and insights. Develop and maintain data models, dashboards, and reports to visualize data findings. Utilize statistical and analytical tools to perform data analysis and generate insights. Collaborate with project teams to understand data requirements and deliver relevant analytical solutions. Ensure data accuracy and integrity by performing data validation and quality checks. Enable Skills-Based Hiring No Primary Skill Required for the Role SQL Level Required for Primary Skill Advanced (6-9 years experience) Additional Skills Requested for Role Skill (optional) Level (optional) Criteria (optional) SQL Advanced (6-9 years experience) AWS Databricks Intermediate (3-5 years experience) Amazon Web Services (AWS) Intermediate (3-5 years experience) Data Build Tool (DBT) Intermediate (3-5 years experience) Data Governance Intermediate (3-5 years experience) MetaData Repository Advanced (6-9 years experience) GenAI Prompt Engineering Intermediate (3-5 years experience) Additional Details for Role The resources will be responsible for supporting the following activities: Inventory metadata and source data across all databases in scope ( FN, FR to start with) Understand and document detailed input sources, data lineage, data movement, controls, and downstream reporting dependencies. Compare data elements across FN, FR, AVD, LTC, and GPR to identify common fields, differences, and normalization needs. Compare source system inputs to what currently exists in the cloud / Databricks environment. Identify data gaps, quality issues, missing attributes, control gaps, and reconciliation needs. Support the creation of a data dictionary, including definitions, naming conventions, metric definitions, and business rules. Partner with the Data Architect, Data Modeler, Pipeline Engineers, database SMEs, actuarial SMEs, and project leadership to support Bronze Layer readiness and future-state data design. The ideal resource should have strong data analysis and data stewardship skills, including experience with data profiling, metadata documentation, source-to-target mapping, data dictionaries, reconciliation, and working with technical and business SMEs. An actuarial or valuation background would be highly valuable since this work will directly support actuaries and Controllers within OCA.

EEO:

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