Data Analyst - Analytics & Data Operations
ACL Digital, Alpharetta, GA, United States
Data Analyst - Analytics & Data Operations
bout the Role
We are seeking a
Data Analyst
who will play a critical role in
delivering reliable insights , working closely with stakeholders, and ensuring data accuracy across the organization. This role goes beyond traditional reporting; the analyst will
ctively investigate and resolve data issues , collaborate with
cross-functional teams , and provide operational support for analytics systems. The ideal candidate is analytically strong, detail-oriented, comfortable working with ambiguity, and capable of balancing
business analysis with data operations and system support .
Key Responsibilities
nalytics & Business Insights
Partner with business and technical stakeholders to understand objectives and translate them into clear analytical requirements
Perform ad-hoc and recurring analyses to support business decision-making
nalyze large datasets to identify trends, risks, anomalies, and opportunities
lign and maintain data definitions, metrics, and business rules across teams
Present insights through dashboards, reports, and clear written or verbal summaries to both technical and non-technical audiences
Data Quality, Issue Resolution & Root Cause Analysis
Proactively identify, investigate, and resolve data discrepancies across source systems, pipelines, and downstream reporting
Perform root-cause analysis in collaboration with data engineering, platform, application, and business teams
Validate fixes, implement preventative controls, and ensure issues do not recur
ct as a primary point of contact for data-related issues, troubleshooting, and inquiries
Data Operations & Systems Support
Monitor data pipelines, dashboards, and jobs for failures or abnormal behavior
Support analytics and reporting systems during incidents, outages, or data availability issues
Conduct post-deployment testing and validation to ensure data accuracy and system stability as needed
Identify opportunities to improve automation, monitoring, alerting, and data workflows
Required Qualifications
7+ years of experience as a Data Analyst or Analytics-driven role
Strong proficiency in SQL or Python (required)
Experience working with databases and large, complex datasets
Strong experience with data visualization or reporting tools (Power BI, Tableau, or similar)
Expertise with modern data platforms and analytics stacks (e.g., Azure, AWS, Databricks, Snowflake)
Solid understanding of data validation, data quality, and reconciliation techniques
Demonstrated ability to independently investigate complex data issues from source systems through reporting layers
Strong analytical, critical-thinking, and problem-solving skills
Excellent communication skills with the ability to work effectively across technical and non-technical teams
Preferred / Nice-to-Have Qualifications
Bachelor's or Master's degree in Business, Analytics, Data Science, Computer Science, Statistics, Math or a related field
Familiarity with cloud data warehouses and ETL/ELT tools
Exposure to data transformation tools (e.g., dbt)
Experience supporting production analytics systems or data platforms
Knowledge of basic statistics and experiment analysis (e.g., A/B testing)
Comfort participating in off-peak deployments and releases when needed
bout the Role
We are seeking a
Data Analyst
who will play a critical role in
delivering reliable insights , working closely with stakeholders, and ensuring data accuracy across the organization. This role goes beyond traditional reporting; the analyst will
ctively investigate and resolve data issues , collaborate with
cross-functional teams , and provide operational support for analytics systems. The ideal candidate is analytically strong, detail-oriented, comfortable working with ambiguity, and capable of balancing
business analysis with data operations and system support .
Key Responsibilities
nalytics & Business Insights
Partner with business and technical stakeholders to understand objectives and translate them into clear analytical requirements
Perform ad-hoc and recurring analyses to support business decision-making
nalyze large datasets to identify trends, risks, anomalies, and opportunities
lign and maintain data definitions, metrics, and business rules across teams
Present insights through dashboards, reports, and clear written or verbal summaries to both technical and non-technical audiences
Data Quality, Issue Resolution & Root Cause Analysis
Proactively identify, investigate, and resolve data discrepancies across source systems, pipelines, and downstream reporting
Perform root-cause analysis in collaboration with data engineering, platform, application, and business teams
Validate fixes, implement preventative controls, and ensure issues do not recur
ct as a primary point of contact for data-related issues, troubleshooting, and inquiries
Data Operations & Systems Support
Monitor data pipelines, dashboards, and jobs for failures or abnormal behavior
Support analytics and reporting systems during incidents, outages, or data availability issues
Conduct post-deployment testing and validation to ensure data accuracy and system stability as needed
Identify opportunities to improve automation, monitoring, alerting, and data workflows
Required Qualifications
7+ years of experience as a Data Analyst or Analytics-driven role
Strong proficiency in SQL or Python (required)
Experience working with databases and large, complex datasets
Strong experience with data visualization or reporting tools (Power BI, Tableau, or similar)
Expertise with modern data platforms and analytics stacks (e.g., Azure, AWS, Databricks, Snowflake)
Solid understanding of data validation, data quality, and reconciliation techniques
Demonstrated ability to independently investigate complex data issues from source systems through reporting layers
Strong analytical, critical-thinking, and problem-solving skills
Excellent communication skills with the ability to work effectively across technical and non-technical teams
Preferred / Nice-to-Have Qualifications
Bachelor's or Master's degree in Business, Analytics, Data Science, Computer Science, Statistics, Math or a related field
Familiarity with cloud data warehouses and ETL/ELT tools
Exposure to data transformation tools (e.g., dbt)
Experience supporting production analytics systems or data platforms
Knowledge of basic statistics and experiment analysis (e.g., A/B testing)
Comfort participating in off-peak deployments and releases when needed