Data Analyst – Data Integration & Enablement

A leading consulting firm is seeking a Data Analyst - Data Integration & Enablement for a 6 month contract to hire role. Position Description **Help Build the Trusted Data Foundation Behind Enterprise Analytics** Seeking a motivated **Data Analyst - Data Integration & Enablement** to join our team supporting a major financial services client. In this role, you will help build and strengthen the trusted data foundation that supports financial and regulatory reporting, enterprise analytics, and data-driven innovation. This is an excellent opportunity for a data professional who enjoys working at the intersection of **business, data, and technology**. You will use **SQL and Python** to analyze complex datasets, profile source systems, define data integration requirements, validate data quality, and help ensure information is accurate, traceable, and ready for downstream reporting and analytics. You will collaborate with business stakeholders, data engineers, architects, and analysts to integrate data across modern enterprise platforms, including the **Enterprise Data Warehouse, Data Lake, Data Mesh, and Operational Data Store (ODS)**. You will also contribute to data modernization initiatives and gain exposure to technologies such as **dbt, Databricks, Google Cloud Platform (GCP), and AI/GenAI-enabled solutions**. **Location:** This position is based onsite at the client location in **Salt Lake City, UT**. Your future duties and responsibilities How you'll make an impact * Partner with business and technology stakeholders to understand business needs and translate them into clear, actionable data integration, reporting, and analytics requirements. * Profile and analyze source systems, data structures, and business rules using **SQL and Python** to identify data relationships, anomalies, quality issues, and integration requirements. * Analyze and document **source-to-target data flows** supporting the Enterprise Data Warehouse, Data Lake, Data Mesh, ODS, and downstream reporting and analytics solutions. * Define and maintain **source-to-target mappings, transformation rules, metadata, business definitions, and data lineage** to improve data transparency, traceability, and regulatory compliance. * Develop and execute comprehensive data validation and testing activities, including data reconciliation, transformation validation, test cases, and data quality controls. * Develop and enhance automated processes using SQL, Python, and modern data technologies to improve the efficiency of data profiling, validation, reconciliation, and reporting. * Collaborate with data engineers, architects, business analysts, and end users to troubleshoot data issues, perform root cause analysis, and ensure delivered solutions meet business and functional requirements. * Contribute to data modernization and continuous improvement initiatives using technologies and approaches such as **dbt, Databricks on GCP, Data Mesh, and AI/GenAI**. * Promote data quality and documentation best practices, share knowledge across the team, and provide guidance or mentorship to team members as appropriate. Required qualifications to be successful in this role What you'll bring * Bachelor's degree in **Data Analytics, Computer Science, Information Systems, Business**, or a related discipline, along with **2+ years of experience** in data analysis, data integration, business intelligence, or a related data-focused role. * Strong hands-on **SQL** skills, including complex queries, joins, aggregations, data profiling, transformation analysis, reconciliation, and data validation. * Working proficiency in **Python** for data analysis, automation, data quality validation, and data integration activities. * Experience analyzing source and target data models and documenting **source-to-target mappings, transformation logic, metadata, data lineage, and business rules**. * Solid understanding of **data quality, data testing, reconciliation, ETL/ELT, data integration, and troubleshooting** within enterprise data environments. * Strong analytical and problem-solving skills, with the ability to investigate complex data issues, identify root causes, and recommend solutions. * Strong requirements gathering, documentation, and stakeholder communication skills, with the ability to translate business needs into actionable data requirements. * Ability to collaborate effectively with both business and technology teams in a complex enterprise environment. ## Desired Qualifications * Exposure to modern data platforms and technologies such as **Databricks, dbt, GCP, Enterprise Data Warehouses, Data Lakes, Data Mesh, and Operational Data Stores (ODS)**. * Experience supporting data environments within **financial services, banking, regulatory reporting**, or another highly regulated industry. * Experience coordinating project activities, supporting workstreams, or mentoring team members. * Exposure to **AI/GenAI concepts, AI-enabled data solutions, or prompt engineering**.