Data Analyst – Data Integration & Enablement
The Data Analyst – Data Integration & Enablement at Confidential Client supports a major financial services client by building and maintaining a trusted data foundation for enterprise analytics and regulatory reporting. This role involves analyzing complex datasets using SQL and Python, defining data integration requirements, validating data quality, and collaborating with cross-functional teams to ensure accurate, traceable data flows across modern data platforms. The position is onsite in Salt Lake City, UT, and contributes to data modernization initiatives leveraging technologies like dbt, Databricks, GCP, and AI/GenAI solutions.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, IT Services and IT Consulting.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
What You'll Do
Confidential Client is seeking a Data Analyst focused on Data Integration & Enablement to strengthen the trusted data foundation that supports financial and regulatory reporting, enterprise analytics, and data-driven initiatives. You will work closely with business stakeholders, data engineers, architects, and analysts to analyze source systems, define integration requirements, validate data quality, and document source-to-target mappings and lineage.
- Partner with business and technology stakeholders to translate business needs into clear data integration, reporting, and analytics requirements.
- Profile and analyze source systems, data structures, and business rules using SQL and Python to identify relationships, anomalies, and quality issues.
- Document source-to-target data flows supporting the enterprise data warehouse, data lake, data mesh, and operational data store (ODS).
- Define and maintain source-to-target mappings, transformation rules, metadata, business definitions, and data lineage to improve transparency and traceability.
- Develop and execute comprehensive data validation and testing activities (reconciliation, transformation validation, and test cases).
- Automate profiling, validation, reconciliation, and reporting tasks using SQL, Python, and modern data tooling.
- Collaborate with engineering and architecture teams to troubleshoot data issues and perform root-cause analysis.
- Contribute to data modernization efforts using technologies and approaches such as dbt, Databricks on GCP, Data Mesh, and AI/GenAI-enabled solutions.
- Promote data quality and documentation best practices; share knowledge and mentor team members as appropriate.
Required Qualifications
- Bachelor’s degree in Data Analytics, Computer Science, Information Systems, Business, or related field, plus 2+ years of relevant experience in data analysis, data integration, or business intelligence.
- Strong, hands-on SQL skills: complex queries, joins, aggregations, profiling, transformation analysis, reconciliation, and validation.
- Working proficiency in Python for data analysis, automation, and data quality validation.
- Experience analyzing source and target data models and documenting source-to-target mappings, transformation logic, metadata, and data lineage.
- Solid understanding of data quality, data testing, reconciliation, ETL/ELT, and data integration in enterprise environments.
- Strong analytical and problem-solving skills; ability to investigate complex data issues and recommend solutions.
- Strong requirements-gathering, documentation, and stakeholder communication skills.
- Ability to collaborate effectively across business and technology teams in complex enterprises.
Desired Qualifications
- Exposure to modern data platforms and tools: Databricks, dbt, Google Cloud Platform (GCP), enterprise data warehouses, data lakes, Data Mesh, and ODS.
- Experience supporting data environments in financial services, banking, regulatory reporting, or other highly regulated industries.
- Experience coordinating project activities, supporting workstreams, or mentoring junior team members.
- Familiarity with AI/GenAI concepts, AI-enabled data solutions, or prompt engineering.
Compensation & Benefits
A reasonable estimate of the current U.S. compensation range for this role is $89,600 – $198,400 per year. Actual compensation will be determined based on skills, experience, level, and location, in accordance with applicable law.
Benefits (typical offerings; eligibility and start date depend on assignment with the client):
- Competitive compensation
- Comprehensive insurance options
- 401(k) matching and share purchase opportunities
- Paid time off for vacation, holidays, and sick time
- Paid parental leave
- Learning opportunities and tuition assistance
- Wellness and well-being programs
Other Information
- This role is based onsite at the client location in Salt Lake City, UT.
- Employment offers may be contingent on successful completion of background checks; components vary by assignment and applicable law.
- Confidential Client provides reasonable accommodations to qualified applicants with disabilities; contact your Careertakes recruiter for assistance and details.
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
If you have questions about how your data is used, please contact us directly.
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