Role Description The Senior Reporting Analyst – GTM supports Lexipol’s Sales and Marketing teams by delivering reporting, analysis, and insights on pipeline performance, sales activity, and revenue trends within a subscription-based SaaS model. This role focuses on building reliable reporting, analyzing sales funnel performance, and helping stakeholders better understand key drivers of pipeline and revenue. You will work cross-functionally to provide visibility into performance and support data-informed decision-making. What You’ll Do - Reporting & Analysis (60%) - Build and maintain Power BI dashboards that provide visibility into: - Pipeline health and coverage - Sales performance and conversion rates - Deal velocity and stage progression - ARR contribution from new business - Analyze end-to-end sales funnel performance, from lead through closed-won - Develop reporting that connects pipeline activity to revenue outcomes - Conduct analyses on: - Conversion rates across sales stages - Sales cycle trends and bottlenecks - Pipeline quality and deal progression - Marketing contribution to pipeline - Support recurring reporting needs and help improve reporting accuracy and consistency - Enable self-service reporting for GTM teams - Insights & Business Support (30%) - Collaborate with Sales and Marketing stakeholders to understand reporting needs and performance trends - Provide insights into pipeline performance, sales activity, and revenue trends - Support business reviews with data and reporting - Help identify trends, risks, and opportunities within pipeline and sales performance - Contribute to improving visibility into key GTM metrics and performance indicators - Collaboration (10%) - Work with stakeholders to align on pipeline definitions, funnel stages, and reporting metrics - Partner with Data Engineering to ensure reliable and consistent data from Salesforce - Act as a bridge between business users and technical teams for reporting needs Qualifications - 5+ years of experience in analytics, business intelligence, or reporting roles - Experience supporting Sales, Marketing, or GTM teams - Experience working in a B2B SaaS or subscription-based environment - Strong understanding of sales and pipeline metrics, such as: - Pipeline coverage - Conversion rates - Sales cycle length - Win rates - Experience working with Salesforce data (Opportunities, Leads, Campaigns, Accounts) - Strong SQL skills with experience querying data in AWS Redshift - Proficiency in Power BI, including data modeling and dashboard development - Ability to translate data into clear, actionable insights - Strong communication skills and ability to work cross-functionally Requirements - Experience analyzing SaaS metrics such as ARR or MRR - Experience working with cloud data environments - Experience building scalable reporting solutions Benefits - Competitive base salary - Monthly, quarterly, or annual incentive - Comprehensive benefits package including 401(k) with Company match - Flexible paid time off plan - Base compensation of $115,000 plus an annual performance-based bonus

• Support analysis of commercial and media data • Design and maintain dashboards and reports in Power BI, Data Studio / Looker Studio • Organize and structure semi-automated data bases (BigQuery, Looker, Power BI, or Google Sheets) • Perform comparative analyses across time periods, identifying patterns and opportunities • Validate hypotheses using data and generate actionable insights • Support the preparation of analytical presentations in PPT • Work with media, performance and business teams on data interpretation • Ensure organization, quality and reliability of information • Meet deadlines and manage priorities in a remote work environment

Role Description As a Lead BI Analyst (19011), you’ll be a key driver of our analytics foundation. You will transform raw event streams and operational datasets into reliable, actionable insights that shape company strategy. You’ll own complex SQL pipelines, design KPI frameworks, and deliver dashboards used daily by leadership. Beyond technical skills, you’ll help structure how the BI function scales — codifying best practices, mentoring analysts, and collaborating cross-functionally. Responsibilities and Duties - Build and maintain layered analytical models across device lifecycle, app usage, and monetization (RPH, ARPU, eCPM, fill-rate, retention). - Reconcile data from multiple operational, product, and revenue systems; surface and track discrepancies. - Create entity-centric models for health, attribution, and longitudinal behavior. - Analyze auction funnels end-to-end (requests → bids → wins → impressions → revenue) and diagnose drop-offs. - Monitor core KPIs with anomaly detection and investigation playbooks to accelerate root-cause analysis. - Develop cohorting, time-series, and survival analyses for growth, churn, and LTV. - Implement anomaly detection and alerting on core revenue/usage KPIs. - Design scalable KPI dashboards in Apache Superset (daily/weekly/monthly) for executives and operators; enable self-serve exploration. - Establish a governed metrics layer/semantic definitions to keep “one source of truth” across teams. - Use templating/parameterization to make dashboards reusable by region, app, device class, cohort, etc. - Align on schemas, SLAs, and data contracts; improve pipeline reliability and query performance. - Build performant rollups/aggregate tables (daily/weekly/hourly) and materialized views for high-traffic queries; set sensible refresh cadences. - Add tests, documentation, and lineage so models are trustworthy and maintainable. Qualifications - 6+ years in BI/Data Analytics (media/CTV/streaming or ad-supported required), owning high-impact dashboards and analyses. - Expert SQL on modern warehouses (Redshift/Snowflake/BigQuery); comfortable with multi-CTE patterns, window functions, tuning, and semi-structured JSON/SUPER parsing. - Strong BI chops (Superset/Tableau/Looker/Mode) with an eye for clarity, performance, and reuse. We currently use Superset for our visualizations. - Fluency in monetization metrics (ARPU, CPM/eCPM, RPH, fill-rate, auction stages) and attribution nuances. - Familiarity with streaming/app lifecycle data (sessions, playback, retention, cohorts) and high-volume event streams. - Excellent communicator: crisp problem framing, clear data stories, and pragmatic recommendations. - Program/project mindset: prioritization, stakeholder alignment, on-time delivery. Nice to Have - Experience using and setting up an “ask-the-data” experience with natural language AI tools, helping stakeholders get quick, reliable insights without deep SQL knowledge in a self-service manner. - Python/R for analytics (pandas, NumPy), notebooks, and lightweight ETL. - dbt for model governance; Airflow/Prefect for orchestration; Git-based workflows and CI for analytics. - Experience with ad tech & measurement (OpenRTB, SSAI, MMPs, household graphs, privacy/consent frameworks). - Time-series forecasting, anomaly detection, and causal inference methods. - Metric layer tools (e.g., dbt Semantic Layer, LookML, Cube/MetricFlow) and documentation/lineage tools. - Spark/PySpark for scale; familiarity with cost/perf tuning in cloud data stacks. Company Description Encora is a global company that offers Software and Digital Engineering solutions. Our practices include Cloud Services, Product Engineering & Application Modernization, Data & Analytics, Digital Experience & Design Services, DevSecOps, Cybersecurity, Quality Engineering, AI & LLM Engineering, among others. At Encora, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.

• Validate data integrity across reporting outputs and source systems within your division • Identify discrepancies and investigate root causes in collaboration with the data engineering team • Ensure all data is reviewed and verified before distribution to stakeholders • Proactively surface data quality issues before they reach leadership or clinical teams • Build and maintain dashboards and reports using Looker, Power BI, Tableau, or similar tools • Translate operational and clinical data into clear, structured insights for non-technical stakeholders • Support recurring reporting needs for divisional leadership • Ensure dashboards are simple, usable, and actively adopted by teams • Apply standardized metric definitions as established and governed by BII leadership • Maintain documentation of reporting logic and calculation methods within your division • Escalate metric inconsistencies or definitional gaps to the BII Director for resolution • Work closely with divisional operations and clinical leadership to understand reporting needs • Act as the primary consumer of data engineering outputs — raise pipeline issues through the BII Director • Contribute to broader BII reporting initiatives as directed by BII leadership