3 дня назад
Data Analyst – Data Integration & Enablement
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Analyst – Data Integration & Enablement (SQL/Python): Analyzing source systems and documenting data flows, mappings, transformations, and lineage for enterprise data warehouses, data lakes, data mesh, and downstream analytics with an accent on data quality, validation, and integration requirements. Focus on automating profiling and reconciliation, troubleshooting complex data issues, and contributing to modernization using dbt, Databricks on GCP, and AI/GenAI.
Location: Salt Lake City, Utah; hybrid onsite and remote
Company
delivers outsourced services and workforce solutions across North America.
What you will do
- Translate business and technology needs into data integration, reporting, and analytics requirements.
- Profile source systems and analyze data structures, relationships, anomalies, and quality issues using SQL and Python.
- Document source-to-target data flows, mappings, transformation rules, metadata, business definitions, and lineage.
- Develop data validation, reconciliation, testing, and data quality controls for enterprise data environments.
- Automate profiling, validation, reconciliation, and reporting processes.
- Collaborate with engineers, architects, analysts, and end users to troubleshoot issues and support data modernization initiatives.
Requirements
- Bachelor’s degree in data analytics, computer science, information systems, business, or a related field, plus 2+ years of relevant experience.
- Strong SQL skills, including complex queries, joins, aggregations, profiling, transformation analysis, reconciliation, and validation.
- Working proficiency in Python for data analysis, automation, data quality, and integration.
- Experience with data models, source-to-target mappings, transformation logic, metadata, lineage, and business rules.
- Understanding of data quality, testing, reconciliation, ETL/ELT, integration, and enterprise troubleshooting.
- Strong analytical, documentation, requirements-gathering, communication, and collaboration skills.
Nice to have
- Exposure to Databricks, dbt, GCP, enterprise data warehouses, data lakes, data mesh, or operational data stores.
- Experience in financial services, banking, regulatory reporting, or another regulated industry.
- Experience coordinating workstreams, supporting projects, or mentoring team members.
- Exposure to AI/GenAI, AI-enabled data solutions, or prompt engineering.
Culture & Benefits
- Permanent direct-hire employment with a 40-hour work week.
- Hybrid onsite and remote work model.
- Eligible employees may receive medical, dental, vision, spending account, life insurance, and voluntary plan options.
- Eligible employees may participate in a 401(k) plan.
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