Data Analyst

Blackbuck Insights; St. Louis (MO); On-site; USD 90,000 - 130,000; Full time

Job summary

Blackbuck Insights in Saint Louis, MO is seeking a Senior Data Analyst for our Wealth Management domain. You will lead data discovery, profiling, and STTM creation for enterprise data platforms, acting as the bridge between business teams and engineering.

You will design SQL-based analyses, document mappings, ensure data quality, and collaborate with ETL developers to translate business rules into technical specs while supporting QA and data governance initiatives.

Qualifications

• 5+ years of hands-on experience as a Data Analyst, Data Modeler, or Technical Business Analyst in enterprise data initiatives.
• Advanced SQL: complex scripts for data extraction and profiling.
• STTM Documentation: explicit STTMs for ETL/ELT pipelines or data migrations.
• Data Quality & Profiling: detect data anomalies and integrity issues.
• Strong communication: translating business logic to engineers and stakeholders.

Responsibilities

• Data Profiling & Pattern Analysis: run SQL across databases, data lakes, and warehouses to analyze distribution and quality.
• Source-to-Target Mapping (STTM): author and maintain mapping documents with rules, data types, keys, and transformations.
• Bridge with developers: walkthroughs of mappings with ETL/engineers to clarify business intent.
• Data Quality & Governance: define validation rules and remediate data gaps across datasets.
• Wealth Management domain mapping: analyze domain data like portfolios, holdings, fees, and trades.

Skills

Advanced SQL

Source-to-Target Mapping

Wealth Management Domain

Jira

Azure DevOps

Data Profiling

Data Pipeline

Relational Modeling

Data Governance

Data Quality

Education

Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Finance, or related quantitative field

Tools

Jira

Azure DevOps

Azure Synapse Analytics

SQL Server

Job description

Saint Louis, United States

BBI is a global data engineering consulting firm that empowers clients to effectively scale and modernize. We combine engineering fundamentals and innovative tools to execute business-critical, end-to-end projects on-time and on-budget. We offer expert services across Data Integration, Data Modernization, Data Migration, Data Architecture, Platform Support, and Application Services. Our goal is to provide business value in the most effective way for our clients so clients can focus on growth.

Job Description

Senior Data AnalystWealth Management Practice | Data Engineering & AnalyticsDOMAINWealth ManagementTECHNICAL COREAdvanced SQL / STTMCLOUD ENVMS Azure (Preferred)EXPERIENCE5+ Years Senior LevelKey Objective: We are seeking a highly analytical Senior Data Analyst to lead data discovery, quality profiling, andSource-to-Target Mapping (STTM) for enterprise wealth management data platforms. This role serves as the critical bridgebetween wealth business teams and engineering developers.Role OverviewAs a Senior Data Analyst in our Wealth Management technology practice, you will play a central role in shapingclient and portfolio data solutions. You will be responsible for navigating complex legacy and modern datastructures—including client profiles, accounts, holdings, transactions, performance metrics, and advisory billingdata.You will perform deep-dive data profiling and pattern analysis using advanced SQL, assess data health and quality,and author comprehensive Source-to-Target Mapping (STTM) documentation. Crucially, you will act as theprincipal functional contact for ETL/Data Engineers, effectively translating business logic into actionableengineering specifications and facilitating clear walkthroughs.Primary Responsibilities

• Data Profiling & Pattern Analysis: Execute complex SQL queries across relational databases, data lakes, andwarehouses to analyze data distribution, evaluate data quality, discover data anomalies, and identify underlyingrelational patterns.
• Source-to-Target Mapping (STTM): Design, author, and maintain robust, granular STTM documents detailingbusiness rules, field transformations, data types, primary/foreign key relationships, and data pipeline logic.
• Developer Collaboration & Bridge: Conduct detailed walkthroughs of mapping documents with engineeringteams (ETL/Data Pipeline developers), clarifying edge cases, data constraints, and business intent to drivesmooth implementation.
• Data Quality & Governance: Establish baseline data quality metrics, define data validation rules, andcollaborate with data governance leads to remediate data discrepancies or gaps across financial datasets.
• Wealth Management Domain Application: Analyze domain-specific data entities, including householdrelationships, investment portfolios, asset classes, custody positions, fee calculations, and trade histories.
• Stakeholder Communication: Articulate data insights, structural risks, and mapping dependencies clearly toboth technical developers and non-technical business stakeholders/product owners.
• Testing & Acceptance Support: Assist QA and engineering teams during sprint cycles by validatingtransformed datasets against original target specifications using customized SQL validation scripts.

Minimum Qualifications

• Experience: 5+ years of hands-on experience as a Data Analyst, Data Modeler, or Technical Business Analyst in enterprise data environment initiatives.
• Advanced SQL Expertise: Proven mastery in writing complex SQL scripts (multi-table JOINs, CTEs, windowfunctions, subqueries, and analytical functions) for data extraction and profiling.
• STTM Documentation: Demonstrated experience creating explicit, comprehensive Source-to-Target Mappings(STTM) for ETL/ELT pipelines, reporting, or data warehouse migrations.
• Data Quality & Profiling: Strong background in identifying data anomalies, missingness, structuralinconsistencies, and data integrity issues.
• Communication Skills: Exceptional verbal and written communication skills with proven experience leadingtechnical specification reviews with software developers and architects.
• Education: Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Finance, or a relatedquantitative field.

Preferred Experience & Skills

• Wealth Management Domain Knowledge: Direct experience working with financial, wealth, investment management, brokerage, or banking data domains (e.g., portfolio management, custodial feeds, advisory accounts).
• MS Azure Cloud Environment: Exposure to or experience working with cloud data platforms on Microsoft Azure (e.g., Azure Synapse Analytics, Azure Data Factory, Azure Data Lake Storage, or Databricks on Azure).
• Modern Data Stacks: Familiarity with modern data modeling concepts (Dimensional, Snowflake, Data Vault) and orchestration workflows.
• Agile/Scrum Framework: Experience working in Agile/Scrum delivery models, managing user stories, and utilizing tools like Jira or Azure DevOps.

Core Skills & Competencies

• Advanced SQL
• Source-to-Target Mapping (STTM)
• Wealth Management Domain
• Jira / Azure DevOps
• Data Lineage
• Data Profiling & Quality
• MS Azure Cloud
• Data Pipeline Specification
• Developer Communication
• Relational Modeling