Senior Data Engineer

LatentView Analytics · Remote

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Last observed by our collector: 8 October 2026 at 11:39 pm IST. This is not a manual review or a confirmation from the employer.

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Collected role description

About LatentView AnalyticsFounded in 2006, LatentView Analytics began with a shared passion for the world of data. Today, over 20 years on, we've grown into a close-knit community of people united by that same drive — solving real business challenges with data and AI. We work with industry leaders worldwide, specializing in end-to-end analytics that goes beyond the buzzwords to deliver genuine business impact. Our focus has stayed consistent since day one: helping clients derive meaningful insights and drive growth through a thoughtful, sustainable approach to data analytics and AI.Role OverviewWe are hiring Data Analysts to work across dashboarding & BI, data modeling, data quality, and analytics functions supporting our clients. You will work closely with business and technical stakeholders to turn data into insights that drive decisions, and the specific focus of your role will be matched to your experience and skills.Key Responsibilities<ul><li style="font-family:'Times New Roman', serif;color:#000000;background-color:transparent;">Design, build, and maintain dashboards, reports, or data models that support business decision-making</li><li style="font-family:'Times New Roman', serif;color:#000000;background-color:transparent;">Write and optimize SQL queries against enterprise data platforms</li><li style="font-family:'Times New Roman', serif;color:#000000;background-color:transparent;">Translate business requirements into clear, actionable analytical solutions</li><li style="font-family:'Times New Roman', serif;color:#000000;background-color:transparent;">Collaborate with cross-functional stakeholders — business, engineering, product, risk, or compliance teams as relevant to the project</li><li style="font-family:'Times New Roman', serif;color:#000000;background-color:transparent;">Ensure data accuracy, consistency, and adherence to governance standards</li><li style="font-family:'Times New Roman', serif;color:#000000;background-color:transparent;">Present insights, dashboards, or recommendations clearly to stakeholders</li></ul>Skills & Experience<ul><li style="font-family:'Times New Roman', serif;color:#000000;background-color:transparent;">3–7 years of relevant experience in Data Analytics, BI, Data Engineering, or Data Science</li><li style="font-family:'Times New Roman', serif;color:#000000;background-color:transparent;">Advanced SQL — complex joins, CTEs, window functions, and query performance optimization</li><li style="font-family:'Times New Roman', serif;color:#000000;background-color:transparent;">Hands-on proficiency in at least one BI/visualization tool — Power BI, Tableau, or Qlik</li><li style="font-family:'Times New Roman', serif;color:#000000;background-color:transparent;">Strong stakeholder management skills — proven ability to work with business teams to shape analytical solutions</li><li style="font-family:'Times New Roman', serif;color:#000000;background-color:transparent;">Python or equivalent scripting (R, PySpark) for data manipulation, automation, or analysis</li></ul>Good to Have(any one)<ul><li style="font-family:'Times New Roman', serif;color:#000000;background-color:transparent;">BI & Dashboard Development: DAX, Power Query / Power BI Report Builder, Row-Level Security, dashboard performance optimization, Snowflake or Azure Databricks</li><li style="font-family:'Times New Roman', serif;color:#000000;background-color:transparent;">Data Modeling & Architecture: Dimensional modeling, data vault methodology, dbt, semantic layer design, data governance and lineage</li><li style="font-family:'Times New Roman', serif;color:#000000;background-color:transparent;">Data Quality & Test Engineering: ETL/pipeline validation, data reconciliation and profiling, automated testing frameworks, CI/CD practices</li><li style="font-family:'Times New Roman', serif;color:#000000;background-color:transparent;">Analytics & Data Science: Statistical techniques (regression, segmentation), A/B testing and experimentation, machine learning exposure, product or e-commerce analytics</li><li style="font-family:'Times New Roman', serif;color:#000000;background-color:transparent;">Analytics Leadership & Consulting: Client/CxO stakeholder engagement, team and project management, mentoring</li></ul>Qualifications<ul><li style="font-family:'Times New Roman', serif;color:#000000;background-color:transparent;">Bachelor's or Master's degree in a quantitative field (Computer Science, Statistics, Engineering, or related) or equivalent practical experience</li><li style="font-family:'Times New Roman', serif;color:#000000;background-color:transparent;">Strong analytical, problem-solving, and communication skills</li></ul>

Collected experience requirement

4 - 8 Years