Data Analyst - Analytics & Data Operations

ACL Digital

$70K — $95K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7+ years of experience as a Data Analyst or in an analytics-driven role
  • Strong proficiency in SQL or Python
  • Experience with databases and handling large, complex datasets
  • Proficient in data visualization tools like Power BI or Tableau
  • Expertise in modern data platforms (e.g., Azure, AWS, Snowflake)
  • Solid understanding of data quality and reconciliation techniques
  • Excellent communication skills for cross-team collaboration

Responsibilities

  • Partner with stakeholders to translate objectives into analytical requirements
  • Conduct ad-hoc and recurring analyses for business decision support
  • Analyze large datasets to identify key trends and opportunities
  • Align data definitions and metrics across teams
  • Present insights through dashboards and clear reports
  • Identify and resolve data discrepancies across systems
  • Monitor data pipelines and support analytics systems during issues

Benefits

  • Flexible work hours
  • Opportunity for continuous learning and development
  • Collaborative and supportive team environment
Full Job Description
Data Analyst - Analytics & Data Operations
About 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 actively 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
Analytics & 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
  • Analyze large datasets to identify trends, risks, anomalies, and opportunities
  • Align 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
  • Act 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

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