Analyst, Data Operations

Bank OZK•Little Rock, AR

About The Position

Supports the development, maintenance, monitoring, and documentation of data pipelines using standard enterprise toolsets under the guidance of more experienced team members. Assists with data observability, basic governance activities, and operational support to help ensure reliable data flow and visibility across the organization. The role works with data engineering teams and business stakeholders to support internal and external data operations, SLA monitoring, notifications, data classification, data quality, and pipeline reliability. It also supports compliance and governance activities related to data security, privacy, and approved data-handling practices. The position may include alternate schedules to cover critical processing periods.

Requirements

Bachelor's degree in Computer Science, Data Science, Information Systems, or a related field, or commensurate work experience.
Basic knowledge of cloud-based data platforms such as Azure, AWS, or GCP and data warehouses such as Snowflake, Redshift, or BigQuery.
Familiarity with tools such as DBT, Power BI, Docker, or similar data and reporting technologies.
Working knowledge of Python and exposure to scripting languages such as Windows PowerShell or Linux Bash.
Working knowledge of SQL and relational databases such as SQL Server, PostgreSQL, or MySQL.
Analytical and problem-solving skills, with an interest in automation, root cause analysis, and data integrity.
Effective verbal and written communication skills.
Ability to work effectively with team members, management, and internal stakeholders, both independently and as part of a team.
Curiosity, accountability, and willingness to learn enterprise data operations practices.
Ability to apply critical thinking and analytical skills to defined problems with appropriate guidance.
Ability to organize work, manage assigned tasks, meet deadlines, and adapt to changing priorities.
Initiative and a proactive approach to accomplishing work tasks and objectives.
Ability to operate customary equipment and technology used in a business environment, with or without accommodation.

Nice To Haves

At least 1 year of experience in data operations, data engineering, quality assurance, analytics, information technology, or a similar role.
At least 1 year of Python development or scripting experience.
At least 1 year of SQL experience.

Responsibilities

Work with data engineering teams and business stakeholders to learn data process dependencies and support internal and external data operations.
Assist with service level agreement monitoring, notifications, data classification, and data quality activities.
Assist with orchestration and monitoring of data pipelines across approved tools and environments using established scheduling practices.
Support integrations for data lineage, observability, classification, and quality metrics in enterprise data tools.
Help set up pipeline monitoring, notifications, restart procedures, and execution settings according to team standards and direction.
Monitor data ingestion, transformation, extracts, integrations, dashboards, and reports for reliability; escalate or assist with troubleshooting issues as appropriate.
Review performance, storage, and cost trends and raise potential issues or improvement opportunities to more experienced team members.
Assist with automating repeatable processes and maintaining visibility into data lineage using approved tools and documented procedures.
Partner with data engineers to support enhancements to data architecture and integration solutions.
Support compliance and governance activities related to data security, privacy, and approved data-handling practices.
Help identify data anomalies, inconsistencies, and integrity issues, following established procedures for documentation, escalation, and resolution.
Document processes, workflows, and best practices for data operations.
Use sound judgment and seek guidance when needed.