Data Analyst – Data Integration & Enablement
Listed on 2026-10-18
-
IT/Tech
Data Analyst, Data Engineering, Data Warehousing
Data Analyst – Data Integration & Enablement #26-03301
- Required Experience:
- Location:
Salt Lake City, UTAH, US - Posted:
Sep 16 2026 - Duration:
Contract
VLink, founded in 2006, is a leading global provider of software engineering services with next-gen technologies and best-in-class talent. Our Headquarters are in the U.S, and we have offices in 7+ countries from North America-Europe to APAC, with expansion plans in the Middle East. With over 1,000 employees working globally, VLink has helped SMBs, and large enterprises achieve their business goals, and gained the trust of Fortune-250 companies.
VLink is 'Great Place to Work® Certified TM' and has been a consistent winner as
- Best Places to Work in CT. Trust, collaboration, and accountability are the three elements that are at the core of VLink's work culture. We value our professionals, providing comprehensive benefits and the opportunity for growth.
Our client is 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.
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…
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