Business Analyst (Data Analyst) - Enterprise Datalakes Implementation Project

Pennant Solutions Group; Richmond (VA); On-site; USD 120,000 - 180,000; Full time

Job summary

Pennant Solutions Group is seeking a Contract Business Analyst to design and deploy a scalable Enterprise Data Lake in Azure. You will translate business needs from Finance, Operations, and Sales into BRDs, FSDs, and user stories, working with Data Engineers, BI developers, and cloud architects.

The role requires 5–15 years of experience, advanced SQL, data profiling, and SAFe/Scrum. You will own the backlog in Jira/Azure DevOps, define ingestion pipelines, and drive data governance and UAT.

Qualifications

• 5–15 years of progressive experience as technical BA, data analyst, or systems analyst.
• Hands-on data lake implementation or migration in enterprise environments.
• Direct Azure data stack exposure: ADLS Gen2, ADF, Synapse, Purview.
• Advanced SQL: multi-table joins, windows, profiling and validation.
• Foundational knowledge of Kimball/Dimensional modeling and Data Vault concepts.
• Experience in SAFe/Agile with backlog tools (ADO/Jira/Confluence).
• Excellent written and verbal communication for technical and leadership audiences.

Responsibilities

• Drive requirements elicitation, BRDs, FSDs, Epics, and user stories with clear acceptance criteria.
• Own backlog grooming and sprint planning with Product Owner and Tech Lead in Jira/ADO.
• Define ingestion pipelines from ERP/CRM sources and manage ADLS Gen2 data zones.
• Collaborate with Data Architects on bronze-to-gold data models and data dictionaries.
• Perform data profiling and validation; support UAT and remediation activities.
• Present architectural runway updates and data pipeline timelines to senior leadership.

Skills

SQL

Data Lake

Azure

Backlog Management

Stakeholder Communication

SAFe/Agile

Data Modeling

Education

CBAP

PMI-PBA

DP-900

DP-203

Tools

Azure DevOps

Jira/Confluence

Azure Data Factory

Azure Databricks

Azure Synapse

Power BI

Job description

Role Overview

We are seeking a highly accomplished, analytical, and delivery-focused Contract Business Analyst to play a pivotal role in designing, architecting, and deploying a scalable, modern Enterprise Data Lake within the Microsoft Azure cloud ecosystem. This strategic initiative serves as the foundational data modernization engine for the entire organization, replacing legacy, siloed data repositories with a unified, governed, and hyper-scalable enterprise data platform.

The successful candidate will act as the vital translator and strategic bridge between diverse business stakeholders (Finance, Operations, Sales, Regulatory Compliance, Product) and technical delivery teams (Data Engineers, Cloud Architects, BI Developers, Data Scientists). You will be tasked with untangling complex legacy data models, capturing nuanced business logic, defining target-state ingestion and reporting requirements, and ensuring that our centralized Azure Data Lake meets the strategic operational and analytical demands of an evolving enterprise.

This is a high-visibility, technical Business Analyst engagement requiring between 5 and 15 years of progressive professional experience. You should be as comfortable writing advanced SQL scripts to validate data profiles as you are facilitating cross-functional workshops with executive stakeholders.

Detailed Roles and Responsibilities

The Business Analyst will own the end-to-end functional lifecycle of the Data Lake build-out, working within a structured Scaled Agile (SAFe/Scrum) framework. Responsibilities fall across several primary disciplines:

1. Requirements Elicitation, Definition, and Backlog Management

• Drive continuous discovery sessions, workshops, and interview cadences with cross-functional business partners to unearth raw data needs, business rules, analytical challenges, and downstream consumption patterns.
• Deconstruct broad enterprise strategies into clear, well-architected Business Requirements Documents (BRDs), Functional Specifications Documents (FSDs), and Epics.
• Author unambiguous, rigorous User Stories complemented by clear Acceptance Criteria utilizing Given-When-Then (Gherkin/BDD) frameworks.
• Manage, groom, and prioritize the Product Backlog in Jira/Azure DevOps, partnering closely with the Product Owner and Technical Lead to plan effective Sprint cycles.
• Map the lineage of critical business metrics, capturing precise transformation formulas, operational constraints, and historical tracking rules.

2. Enterprise Data Lake & Azure Ecosystem Operations

• Collaborate with Data Architects to shape bronze (raw), silver (cleansed/standardized), and gold (business-aggregated) consumption zones within Azure Data Lake Storage (ADLS Gen2).
• Define functional requirements for continuous and batch ingestion pipelines leveraged via Azure Data Factory (ADF) from various source systems, including enterprise ERPs, CRMs (Salesforce), flat-file repositories, and third-party APIs.
• Understand and facilitate technical discussions related to transformations run inside Azure Databricks, Azure Synapse Analytics, and serverless compute models.
• Develop comprehensive Data Dictionaries, Enterprise Data Catalogs, and Source-to-Target Mappings (STTM) with granular field-level transformation instructions.

3. Data Profiling, Analysis, and Validation

• Perform exploratory data analysis and data profiling on source systems using advanced SQL queries to evaluate data cleanliness, completeness, referential integrity, and edge cases.
• Analyze structured, semi-structured (JSON, Parquet, XML), and unstructured datasets to identify anomalies prior to pipeline development.
• Partner with QA engineers and Data Platform leads to build automated and manual data quality validation pipelines against raw vs. enriched layers.
• Design user-facing validation playbooks and coordinate User Acceptance Testing (UAT) execution cycles, identifying defect root causes and driving rapid remediations.

4. Stakeholder Alignment and Change Management

• Serve as the single source of truth for scope clarification during daily standups, architectural design reviews, and sprint planning meetings.
• Prepare and present architectural runway updates, project milestone status, and data pipeline rollout timelines to senior leadership.
• Design training collateral, user documentation, and contextual workflow guides to enable downstream Business Intelligence (BI) and analytics teams to transition smoothly to the Azure Data Lake.

Required Experience and Qualifications

Candidates must possess a rich background combining classical business analysis methodologies with deep technical domain knowledge in data platforms:

• Professional Experience: Minimum of 5 years, up to 15 years, of dedicated experience operating as a technical Business Analyst, Data Analyst, or Systems Analyst within enterprise-scale IT environments.
• Data Lake Expertise: Proven, hands-on experience participating in at least one full lifecycle greenfield implementation or major legacy migration to an Enterprise Data Lake. Demonstrated understanding of data lake concepts (raw vs. curated data, lakehouse architecture, partitions, ingestion frequencies).
• Cloud Ecosystem (Azure): Direct, functional exposure to the Microsoft Azure data stack, specifically Azure Data Lake Storage (ADLS Gen2), Azure Data Factory (ADF), Azure Synapse Analytics, and Microsoft Purview.
• SQL Proficiency: Advanced SQL capabilities. Must possess the ability to write complex queries involving multi-table joins, subqueries, and window functions to audit, profile, and troubleshoot datasets independently.
• Data Modeling Acumen: Foundational grasp of Dimensional Modeling (Kimball), Normalized Schemas (Inmon), and Data Vault concepts to effectively interface with enterprise data modelers.
• Agile Methodologies: Deep familiarity working inside Agile teams (Scrum, Kanban, or SAFe). Demonstrated experience utilizing tools like Azure DevOps (ADO) or Jira/Confluence for requirement traceability and backlog grooming.
• Communication Skills: Exceptional verbal, written, and visualization skills. Proven ability to break down highly technical cloud constraints into clear commercial realities for non-technical leadership.

Preferred (Nice-to-Have) Skills

• Prior experience working alongside Data Science and Advanced Analytics groups, mapping feature stores and machine learning input pipelines.
• Hands-on reporting experience using enterprise Business Intelligence platforms such as Power BI or Tableau to build validation dashboards.
• Exposure to distributed processing frameworks such as Apache Spark, Azure Databricks, or Delta Lake architecture.
• Professional certifications such as CBAP (Certified Business Analysis Professional), PMI-PBA, or Microsoft Certified: Azure Data Fundamentals (DP-900) / Azure Data Engineer Associate (DP-203).