Business Analyst, Data Platform

Business Analyst Data Platform JD-0050

Key Responsibilities

Profile existing IntelliTrans data assets using SQL and Python to understand data quality distributions anomalies and fitness for monetization. Document data lineage system-of-record mappings and known data quality issues for each data product in Databricks Unity Catalog and related tools. Define clear testable data quality acceptance criteria (completeness accuracy timeliness consistency) that engineering and data teams can implement and monitor. Develop and maintain detailed schema documentation and a data dictionary used by product engineering customer success and sales to position and support data products. Validate feasibility of proposed data products and analytics use cases against the actual state of the data highlighting gaps and risks. Conduct stakeholder interviews and workshops with product customer success professional services and customers to elicit refine and prioritize data product requirements. Own the gap analysis between current data/platform capabilities and target data product requirements recommending remediation and enhancement paths. Define and document data contracts between source systems and the platform including required fields semantics quality thresholds and change management expectations. Required Skills Strong experience as a Business Analyst working on data platforms or analytics products preferably in enterprise SaaS environments. Advanced SQL skills including complex joins window functions common table expressions (CTEs) and performance-aware querying. Hands-on data profiling experience to identify gaps anomalies distributions cardinalities and outliers in large datasets. Working knowledge of Databricks Unity Catalog for managing data lineage tags governance metadata and access. Functional proficiency in Python for data exploration and analysis including practical use of Pandas and notebook-based workflows. Experience defining and working with data quality frameworks (completeness accuracy timeliness consistency validity). Proven ability to produce rigorous unambiguous and traceable business and data requirements documentation. Experience creating and maintaining schema documentation data dictionaries and related metadata assets. Familiarity with logistics domain data including concepts such as detention demurrage dwell time ETA and jeopardy events. Demonstrated capability to work effectively in ambiguous discovery-heavy environments where specifications evolve over time. Strong stakeholder management interviewing and communication skills across technical and non-technical audiences. Good to Have Skills Experience working on or with modern data platforms and lakehouse architectures beyond Databricks. Exposure to BI/analytics tools (e.g. Power BI Tableau Looker) for validating and showcasing data products. Knowledge of data governance metadata management and compliance practices in enterprise environments. Understanding of event-driven architectures and streaming data concepts in logistics or supply chain contexts. Familiarity with API-based data contracts and integration patterns (REST JSON webhooks). Experience with Agile/Scrum methodologies and tools such as Jira or Azure DevOps for managing requirements and backlogs. Background in transportation supply chain or logistics SaaS products and related KPIs. Experience Required 5 to 8 years of professional experience as a Business Analyst with a strong focus on data-heavy enterprise SaaS or data platform products

Required Skills:

Business Analyst Experience Advanced SQL Data Profiling Python/Pandas Databricks Unity Catalog Data Quality Frameworks Requirements Documentation Data Dictionary/Metadata Logistics/Supply Chain Domain Stakeholder Management