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Key Responsibilities and Required Skills for Business Operations Analyst

💰 $ - $

OperationsAnalyticsBusiness Intelligence

🎯 Role Definition

The Business Operations Analyst is a cross-functional, data-driven role responsible for improving operational efficiency, building and maintaining reporting and BI solutions, supporting financial and operational forecasts, and partnering with stakeholders across product, finance, customer success and engineering to translate business problems into measurable solutions. This role uses SQL, Excel, BI tools (Tableau, Power BI, Looker), and business acumen to drive decisions, streamline processes, and implement scalable operational playbooks.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Business Analyst / Junior Business Analyst
  • Operations Coordinator or Operations Associate
  • Data Analyst / Reporting Analyst

Advancement To:

  • Senior Business Operations Analyst
  • Operations Manager / Program Manager
  • Head of Business Operations / Director of Operations
  • Product Operations Manager or Strategy Manager

Lateral Moves:

  • Project Manager
  • Product Analyst
  • Customer Success or Account Operations Lead

Core Responsibilities

Primary Functions

  • Design, build, and maintain recurring and ad-hoc operational reports, dashboards, and executive-level scorecards using SQL and BI tools (Tableau, Power BI, Looker) to measure key performance indicators and track business health.
  • Conduct deep-dive analyses into operational metrics (churn, adoption, processing time, capacity, SLA performance) to identify root causes, quantify impact, and recommend actionable process improvements.
  • Partner with finance and FP&A to develop, reconcile, and maintain monthly and quarterly forecasts, variance analyses, and driver-based financial models that inform budgeting and strategic planning.
  • Lead cross-functional projects from problem definition to implementation, including requirements gathering, stakeholder alignment, project plans, KPI tracking, and post-implementation measurement.
  • Translate business questions into repeatable data queries and analytics workflows by writing performant SQL, data joins, aggregations, and documented data definitions to ensure consistency across teams.
  • Create and operationalize standard operating procedures (SOPs), runbooks, and business process documentation to increase consistency, reduce onboarding time, and support scale.
  • Develop and implement automation solutions (scripts, macros, ETL jobs, workflow automation) to reduce manual effort, minimize errors, and accelerate business processes across finance, sales ops, and support functions.
  • Monitor daily/weekly operational dashboards, detect anomalies and trends, and proactively escalate material issues with clear remediation plans and timelines.
  • Conduct A/B and funnel analyses to evaluate product experiments and process changes, providing statistically sound recommendations and communicating findings to product and growth teams.
  • Manage data integrity efforts by reconciling source systems (CRM, billing, ERP, ticketing systems) and partnering with data engineering to resolve discrepancies and improve data lineage.
  • Build capacity planning and workforce forecasting models that inform hiring plans, scheduling, and vendor engagement for operational teams.
  • Lead root cause analysis on operational incidents and implement corrective action items, tracking metrics pre- and post-remediation to validate effectiveness.
  • Prioritize competing operational requests and intake from stakeholders, negotiate scope and timelines, and maintain a transparent backlog of analytics and process improvement initiatives.
  • Support month-end and quarter-end close activities that require operational reconciliations, transaction validation, and reporting required by Finance and Accounting.
  • Develop and maintain pricing, discount, and revenue recognition support materials; model the operational impact of pricing changes and special deals on revenue and margins.
  • Partner with product and engineering to define data requirements for new features, ensure instrumentation is complete, and validate analytics readiness before release.
  • Track vendor performance and SLAs (third-party fulfillment, payment processors, logistics), analyze cost-to-serve, and recommend vendor or contract changes based on performance data.
  • Own customer lifecycle metrics and reporting (onboarding time, time-to-value, renewal drivers) and deliver insights that improve retention, expansion, and customer satisfaction.
  • Facilitate cross-functional working groups to align on operational KPIs, definitions, and improvement roadmaps; run regular business reviews for leadership.
  • Conduct time-and-motion and process mapping studies to identify bottlenecks and propose lean solutions that reduce cycle times and lower operating costs.
  • Build clear, story-driven slide decks and presentations that synthesize complex analyses into executive-ready recommendations with quantitative impact and next steps.
  • Establish and enforce governance for operational data usage, definitions, and access controls to ensure accurate reporting and compliance with internal policies.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis.
  • Contribute to the organization's data strategy and roadmap.
  • Collaborate with business units to translate data needs into engineering requirements.
  • Participate in sprint planning and agile ceremonies within the data engineering team.
  • Provide training and enablement for non-technical stakeholders on dashboards and self-serve analytics.
  • Assist with operational readiness and rollout activities for new product features, pricing, or process changes.
  • Support compliance and audit activities with documented reconciliations and evidence of controls.
  • Maintain an operational knowledge base and FAQ to reduce repetitive queries to the analytics team.

Required Skills & Competencies

Hard Skills (Technical)

  • Advanced SQL for data extraction, transformation, complex joins, window functions, and query optimization.
  • Expert-level Excel skills including pivot tables, advanced formulas, macros/VBA, and modeling techniques.
  • Experience building and maintaining dashboards in Tableau, Power BI, Looker, or similar BI platforms.
  • Strong experience with data modeling concepts, ETL processes, and familiarity with data warehouses (Snowflake, Redshift, BigQuery).
  • Financial modeling and forecasting skills including driver-based models, scenario analysis, and variance attribution.
  • Proficiency with analytics tools and languages (Python or R) for advanced analytics and automation is preferred.
  • Experience integrating and reconciling CRM and ERP systems (Salesforce, NetSuite, Workday, SAP) for operational reporting.
  • Familiarity with event-level analytics, instrumentation, and query tools (Segment, Amplitude, Mixpanel) for behavioral insights.
  • Knowledge of process improvement and lean methodologies (Six Sigma, Kaizen) and change management practices.
  • Experience with project management and collaboration tools (Jira, Asana, Confluence, Smartsheet).
  • Ability to design and implement automation tooling (Airflow, dbt, Zapier) or scripting to reduce manual tasks.
  • Strong data governance and documentation practices: data dictionaries, lineage, and access controls.

Soft Skills

  • Strong business acumen with the ability to translate data into strategic recommendations that influence leadership.
  • Excellent stakeholder management and communication skills, including the ability to present complex analyses to non-technical audiences.
  • Proven problem-solving chops and curiosity; comfortable with ambiguous problems and defining the right analytical approach.
  • High attention to detail with a focus on data accuracy, reproducibility, and clear documentation.
  • Prioritization and time management skills to balance operational fire-drills with long-term improvement projects.
  • Collaborative, team-oriented mindset with the ability to lead cross-functional initiatives without direct authority.
  • Adaptability and resilience in fast-paced, changing environments; comfort with shifting priorities.
  • Strong organizational skills and the ability to maintain a structured backlog and deliverables list.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor’s degree in Business, Finance, Economics, Statistics, Computer Science, Engineering, or related field.

Preferred Education:

  • Bachelor’s plus advanced degree (MBA, MS in Analytics, or related) or relevant certifications (CBIP, Lean Six Sigma, PMP).

Relevant Fields of Study:

  • Business Administration
  • Finance or Accounting
  • Economics
  • Data Science / Analytics / Statistics
  • Industrial Engineering / Operations Research
  • Computer Science / Management Information Systems (MIS)

Experience Requirements

Typical Experience Range:

  • 2–5 years of related experience in business operations, analytics, financial operations, or strategy roles.

Preferred:

  • 3–7+ years in operations or analytics within SaaS, fintech, e-commerce, or large-scale service environments, with demonstrable experience in SQL, BI dashboards, process improvement, and cross-functional program delivery.
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