Data Operations Analyst

Location: Lahore | Work Mode: On-site Experience: 5+ Years Role Overview The Data Operations Analyst serves as the technical foundation of the Business Operations & Intelligence (BOI) function. This role is responsible for ensuring that the data powering dashboards, scorecards, and executive reports is accurately sourced, consistently structured, rigorously validated, and refreshed on schedule. BOI operates across a large and growing client portfolio, with operational and financial data coming from multiple practice management systems, billing platforms, EHRs, clearinghouses, and reporting environments. The core challenge of this role is to bring these diverse and inconsistent data sources into a reliable, structured, and usable reporting environment. The ideal candidate enjoys solving complex data problems and understands that the quality of business intelligence depends fundamentally on the integrity of the underlying data. Key Responsibilities Own the extraction, consolidation, normalization, and preparation of operational and financial data from multiple source platforms. Manage data feeds from practice management systems, EHRs, clearinghouses, billing platforms, and reporting tools across multiple client accounts. Establish and maintain daily, weekly, and monthly data refresh processes. Design and maintain automated data pipelines using SQL, Power Query, Power Automate, and scripting tools. Configure and maintain API-based data extraction workflows and coordinate with IT/R&D teams for deeper integrations. Develop data validation routines, including completeness checks, threshold monitoring, anomaly detection, and cross-source reconciliation. Identify and resolve data inconsistencies, missing records, schema changes, and calculation discrepancies before they reach the analytical layer. Maintain the BOI data repository and ensure that data remains accurate, complete, current, and structured for analytical use. Convert documented data requirements, field mappings, and refresh logic into reliable and maintainable data infrastructure. Maintain comprehensive documentation covering data sources, extraction methods, field definitions, refresh schedules, transformations, and known limitations. Proactively identify source-system changes, extraction failures, and data-quality issues before they affect leadership-facing reports. Work closely with the Business Intelligence Analyst to ensure a clean, documented, and repeatable transition from validated data to analytical outputs. Required Qualifications & Experience Education Bachelor's degree in Information Systems, Computer Science, Business Intelligence, Data Engineering, or a related technical discipline. Formal training in database management, data architecture, or systems integration is an advantage. Experience 5+ years of experience in Data Operations, MIS, Business Intelligence Support, Data Engineering, or a related field. Proven experience working with multiple heterogeneous data sources, schemas, formats, and refresh frequencies. Experience building or maintaining systems that consolidate diverse data sources into a structured reporting environment. Experience in a multi-client or shared-services environment is preferred. Experience working with US healthcare data, Revenue Cycle Management (RCM), practice management systems, or healthcare platforms is a strong advantage. Experience translating analytical requirements into structured and maintainable data infrastructure. Technical Skills SQL & Databases Strong working knowledge of SQL, including: Multi-table joins Conditional aggregations Window functions Data transformation logic Experience with Microsoft SQL Server or PostgreSQL. Excel & Power Query Advanced Excel proficiency, particularly Power Query and data modeling. Ability to develop reusable transformation templates and structured extraction workflows rather than relying on manual spreadsheet maintenance. Power BI Ability to build and maintain Power BI semantic/data models. Strong understanding of: Table relationships DAX measures Dataset structures Analytical data modeling Automation & Integration Experience with Power Automate for scheduled extraction, refresh, and workflow automation. Understanding of REST APIs, including authentication and working with JSON/XML responses. Ability to develop repeatable API-based extraction processes. Python or PowerShell scripting experience for data automation and file-processing tasks is a strong advantage. Familiarity with RPA tools for scenarios where API or direct database access is unavailable. Data Architecture Working knowledge of data warehouse concepts, including: Dimensional modeling Staging layers Raw vs. transformed data Reporting-ready datasets Ability to contribute to scalable data infrastructure as the BOI function grows. Data Quality & Governance Design and execute validation processes that identify: Missing records Data anomalies Schema drift Calculation inconsistencies Source-to-source discrepancies Develop scalable quality controls as the number of client data feeds increases. Maintain formal documentation for every data stream supporting BOI reporting. Monitor source-system changes and proactively assess their impact on data availability and reporting accuracy. Escalate data-quality issues before they impact downstream dashboards or executive reports. Communication & Collaboration Ability to explain technical and data-quality issues in clear business and operational terms. Act as a key coordination point with IT/R&D and Software Development teams for integrations, APIs, and data-access requirements. Translate BOI requirements into clear technical specifications. Evaluate proposed technical solutions and ensure they meet business requirements. Work closely with the Business Intelligence Analyst as a core BOI team: Data Operations Analyst: Ensures data is structured, validated, and reliable. Business Intelligence Analyst: Converts that data into analysis, intelligence, and business recommendations. Ideal Candidate The ideal candidate is someone who can independently manage the data operations lifecycle—from extraction and transformation through validation, automation, and reporting readiness. They should be comfortable working with imperfect data, multiple systems, changing requirements, and technical stakeholders, while maintaining a strong focus on accuracy, reliability, documentation, and scalability. Location: Lahore Work Mode: On-site Experience: 5+ Years Healthcare / RCM Experience: Preferred, but not mandatory Education Middle School (Preferred) Experience: Data Operations Analyst: 5 years (Preferred) Location: Lahore Johar Town (Preferred) Work Location: In person