Data Solutions Analyst – Data Warehousing & Migration

Job Title: Data Solutions Analyst – Data Warehousing & Migration
Location: Onsite role with hybrid presence twice a week at Arlington TX
Contract: 4+ Months

Job Description:
Data Architecture, data Warehousing, Databricks, Requirement Gathering, SQL

Role Summary
We are seeking a highly experiencedLead Data Solutions Analyst / Technical Data Project Manager with 10+ years of hands-on experience in enterprise Data Warehousing, Data Modeling, and Data Analytics.
This role is not constrained to a single technology stack; rather, it demands strong foundational technical acumen in data architecture, advanced SQL proficiency, and the analytical maturity to bridge business needs with engineering delivery.
In this role, you will lead the initial discovery, requirements gathering, and analysis of current enterprise data products. You will partner with business stakeholders currently consuming data from legacy platforms (such as Oracle Exadata), collaborate with new source system teams (such as Helix), author comprehensive Source-to-Target Mappings (STTM), mentor junior analysts, and guide data engineers in designing robust target data models and pipelines on our modern Analytics Platform.
 
Key Responsibilities
1. Data Product Discovery & As-Is Analysis
Conduct deep-dive analysis into legacy data products, reports, and data pipelines to understand existing data flows, consumption patterns, and underlying schemas.
Engage directly with Exadata business user teams and report owners to catalog existing tables, columns, logic transformations, and technical dependencies.
Document current business rules, data definitions, and reporting requirements to ensure parity and enhancement in target systems.
2. Source System Discovery & Interface Alignment
Partner with the new core source platform engineering teams (Helix) to analyze target schemas, APIs, change data capture (CDC) mechanisms, and event schemas.
Identify gaps between legacy attributes and newly available data points in the Helix source system.
Lead discovery sessions to resolve data discrepancies, business terminology mismatches, and data quality issues between source and consumer domains.
3. Source-to-Target Mapping (STTM) & Design Leadership
Formulate and document detailed, production-grade Source-to-Target Mapping (STTM) specifications, detailing transformation logic, business rules, lookup criteria, primary/foreign keys, and data lineage.
Establish standard STTM templates, review frameworks, and best practices across the initiative.
Mentor and oversee junior analysts and data engineers in drafting and validating STTM artifacts.
4. Technical Delivery & Developer Advisory
Serve as the functional and technical SME for data engineering squads building ingest and curation pipelines into the Analytics Platform.
Provide architectural and schema design guidance to developers, ensuring target dimensional tables (facts, dimensions, curated data marts) align with business consumption needs and performance requirements.
Participate in schema design reviews, backlog grooming, sprint planning, and acceptance testing of transformed datasets.
5. Stakeholder Management & Technical Facilitation
Facilitate recurring cross-functional technical alignment sessions between upstream source teams (Helix), core Data Engineering, and downstream business/analytics users.
Translate complex data nuances and architectural challenges into actionable business context for decision-makers.
Track dependencies, proactively mitigate technical risks, and ensure milestone commitments are met across teams.
 
Required Qualifications & Experience
Total Experience: 10+ years of professional experience across Data Warehousing, Business Intelligence, Data Engineering, or Technical Data Project Management.
SQL & Data Proficiency: Advanced SQL skills with extensive experience analyzing complex relational schemas, querying multi-terabyte data stores, and writing validation queries.
Data Warehousing Acumen: Deep conceptual understanding of dimensional modeling (Star and Snowflake schemas), Fact/Dimension tables, Slowly Changing Dimensions (SCD types), normalization/denormalization, and Data Mart architecture.
Requirements & Mapping: Proven track record of authoring end-to-end, rigorous Source-to-Target Mapping (STTM) documentation for complex data migration or integration programs.
Data Migration Experience: Hands-on experience working with enterprise data platforms (e.g., Oracle Exadata, Snowflake, Databricks, Teradata, BigQuery, or Redshift) and transitioning legacy schemas to modern target platforms.
Mentorship & Leadership: Demonstrated capability to mentor junior data analysts/engineers, lead peer reviews, and define technical documentation standards.
Communication & Facilitation: Exceptional verbal, written, and presentation skills with a demonstrated ability to steer technical discussions among architects, developers, and non-technical business leaders.
 
Preferred / Nice-to-Have Qualifications
Exposure to Oracle Exadata environments and modern Cloud Analytics platforms (e.g., Databricks Lakehouse, AWS, Azure Synapse, Snowflake).
Prior experience working as a Technical Product Manager (TPM), Product Owner, or Lead Data Architect on large-scale core system migration initiatives.
Familiarity with Data Governance, Data Cataloging, and Data Lineage tooling (e.g., Collibra, Alation, Purview, Unity Catalog).
Working knowledge of Agile/Scrum delivery methodologies and toolsets (Jira, Confluence).
 
Key Competencies
Analytical Rigor: Ability to trace complex enterprise business logic back to raw source attributes with precision.
Bridge Builder: Capacity to translate business user requests into technical pipeline specifications and developer-ready tasks.
Pragmatic Problem Solver: Comfortable navigating ambiguous or legacy data environments where source documentation may be incomplete.
Delivery-Oriented: Focused on data quality, data integrity, and business adoption of newly released data assets.