Job Opening: Contract Business Analyst / Data Analyst – Enterprise Data Lake Implementation

Position Type: Contract (12 Months, with high potential for extension)

Location: Hybrid - 3 days per week in Richmond, VA ONSITE (Candidates must reside in Richmond, VA)

Experience Level: Mid-Senior to Lead Level (5 to 15 Years of Experience)

Domain Focus: Enterprise Data Lake Architecture, Data Modeling, Cloud Analytics

Primary Technology Stack: Microsoft Azure (ADLS Gen2, Synapse, Databricks, Purview), SQL, Power BI, Advanced Analytics

About the Role

We are actively seeking a highly skilled, results-oriented Contract Business Analyst / Data Analyst with deep functional and technical expertise in large-scale Enterprise Data Lake Implementations . In this role, you will bridge the gap between complex enterprise business requirements and modern cloud data engineering architectures.

The successful candidate will serve as the analytical nexus within a multi-phased modernization program aimed at centralizing enterprise data into a scalable Microsoft Azure Data Lake ecosystem. We require a specialized professional with between 5 and 15 years of progressive experience who excels at data profiling, metadata management, source-to-target mapping, business process re-engineering, and validation of distributed data pipelines. You will collaborate closely with enterprise business stakeholders, data engineers, enterprise architects, and analytics teams to turn raw business inputs into robust, high-performance data lake products.

Key Objectives & Project Scope

This initiative involves migrating disparate legacy operational databases, ERPs, CRM systems, and external third-party feeds into a modern, centralized Azure Data Lake architecture. Core project goals include:

• Decommissioning legacy siloed data marts and transitioning workloads to a unified Azure Data Lake Storage (ADLS Gen2) environment.
• Establishing standardized Bronze (Raw), Silver (Curated/Cleansed), and Gold (Business Aggregates) layers to serve downstream BI and Advanced Analytics use cases.
• Enforcing strict data governance, lineage tracking, and data quality frameworks across complex transactional and analytical pipelines.
• Accelerating data democratization by providing business units with self-service analytics models supported by optimized Azure Synapse and Power BI assets.

Detailed Roles & Responsibilities

1. Business & Technical Requirements Engineering

• Lead discovery sessions, workshops, and structured interviews with enterprise cross-functional stakeholders to capture data demands, consumption patterns, and analytical needs.
• Translate ambiguous, high-level business requirements into precise technical epics, user stories, and acceptance criteria tailored for an Agile data platform delivery team.
• Construct end-to-end functional requirement documents (FRDs), technical design specifications, and business requirement documents (BRDs).
• Define and document granular source-to-target mapping (STTM) matrices detailing ingestion frequency, transformation rules, filtering criteria, and business logic.

2. Advanced Data Analysis, Profiling & Modeling

• Perform deep-dive data profiling on diverse data sources (RDBMS, NoSQL, Semi-structured JSON/XML, flat files) to detect data anomalies, schema drift, nullability patterns, and cardinality issues.
• Write complex SQL queries, analytical functions, and stored procedures across multi-terabyte data stores to validate historical trends and edge cases.
• Partner with Data Architects to design multidimensional schemas (Star, Snowflake) and logical/physical data models for the Gold/Consumption layers within the Azure ecosystem.
• Establish and document clear definitions for Enterprise Key Performance Indicators (KPIs), metrics, and attributes to drive a unified business semantic layer.

3. Azure Data Lake Ecosystem Collaboration

• Work in lockstep with Data Engineers leveraging Azure Data Factory (ADF), Azure Databricks, and Azure Synapse to ensure data ingestion pipelines match business rules exactly.
• Participate in defining and evaluating data lake partitioning strategies, file formats (Parquet, Delta Lake), and lifecycle management policies to balance performance with cost optimization.
• Support metadata management and data cataloging processes using platforms like Microsoft Purview, ensuring data lineage is continuously tracked and maintained.

4. Data Governance, Quality & Compliance

• Formulate comprehensive Data Quality (DQ) metrics, rules, and threshold frameworks; orchestrate automated data profiling and exception handling processes.
• Ensure compliance with enterprise data privacy mandates, enterprise access governance, and regulatory standards (e.g., GDPR, CCPA, HIPAA, SOC2) during data ingestion and curation.
• Identify data ownership models and partner with designated Data Stewards to resolve structural and semantic discrepancies across source systems.

5. Quality Assurance, User Acceptance Testing (UAT) & Deployment

• Author and execute rigorous test scripts, validation queries, and acceptance test plans to reconcile source data against target lakehouse layers.
• Coordinate and facilitate formal User Acceptance Testing (UAT) cycles with enterprise business users, logging defects, orchestrating triage sessions, and managing backlogs to resolution.
• Develop training materials, data dictionaries, and operational runbooks; conduct knowledge-transfer sessions to accelerate user adoption of modern data assets.

Required Qualifications & Technical Expertise

• Work Experience: 5 to 15 years of demonstrable experience as a Business Analyst, Data Analyst, or Systems Analyst, specifically within enterprise data warehousing and big data initiatives.
• Data Lake Experience: Direct involvement in at least one full-lifecycle Enterprise Data Lake / Lakehouse design, development, or migration initiative.
• Microsoft Azure Ecosystem: Comprehensive, hands-on functional and technical understanding of:
• Advanced Querying & Data Manipulation: Expert-level SQL proficiency (complex joins, window functions, recursive queries, query optimization).
• Source-to-Target Mapping (STTM): Exceptional ability to generate exhaustive STTM documentation capturing transformations, joins, aggregate logic, and metadata.
• Data Modeling: Strong understanding of relational data modeling, Data Vault 2.0, dimensional modeling (Kimball methodology), and medallion (Bronze/Silver/Gold) architectures.
• Business Intelligence (BI): Familiarity with reporting tools, especially Power BI (DAX, Power Query), to prototype dashboards and validate data pipelines visually.
• Agile Methodologies: Deep expertise operating inside Agile, Scrum, or Scaled Agile (SAFe) software development lifecycles utilizing Jira, Azure DevOps, or Confluence.
• Education: Bachelor's or Master's degree in Computer Science, Information Systems, Business Analytics, Data Management, or a related discipline.

Preferred / Nice-to-Have Skills

• Relevant Industry Certifications:
  • Microsoft Certified: Azure Data Fundamentals (DP-900)
  • Microsoft Certified: Azure Data Engineer Associate (DP-203)
  • Microsoft Certified: Power BI Data Analyst Associate (PL-300)
  • Certified Business Analysis Professional (CBAP) or PMI-PBA
• Working knowledge of scripting languages (Python, PySpark, or R) for advanced data exploration and validation.
• Experience handling change management and data governance frameworks in regulated sectors (Finance, Healthcare, Insurance, or Retail).

Soft Skills & Professional Attributes

• Exceptional Communication: Articulate complex architectural and analytical concepts to non-technical business partners, executive leadership, and deep technical engineers alike.
• Analytical Mindset: High attention to detail with an investigative approach to data discrepancies and missing business logic.
• Stakeholder Negotiation: Proven track record of managing competing priorities, scoping constraints, and dynamic requirements in enterprise environments.
• Autonomous Driver: Self-starter capable of navigating ambiguity, establishing alignment, and executing tasks on schedule within matrixed contract environments.

Why Join This Initiative?

This project represents a critical strategic investment in modern data architecture. You will be placed at the core of a high-visibility, mission-critical transformation where your contributions directly shape how the enterprise governs, surfaces, and consumes analytical data for years to come. We offer a competitive rate structure, exposure to top-tier enterprise cloud architectures, and a collaborative team of experienced data practitioners.