Senior Data Engineer

About LatentView Analytics

Founded 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 Overview

We 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

• Design, build, and maintain dashboards, reports, or data models that support business decision-making

• Write and optimize SQL queries against enterprise data platforms

• Translate business requirements into clear, actionable analytical solutions

• Collaborate with cross-functional stakeholders — business, engineering, product, risk, or compliance teams as relevant to the project

• Ensure data accuracy, consistency, and adherence to governance standards

• Present insights, dashboards, or recommendations clearly to stakeholders

Skills & Experience

• 3–7 years of relevant experience in Data Analytics, BI, Data Engineering, or Data Science

• Advanced SQL — complex joins, CTEs, window functions, and query performance optimization

• Hands-on proficiency in at least one BI/visualization tool — Power BI, Tableau, or Qlik

• Strong stakeholder management skills — proven ability to work with business teams to shape analytical solutions

• Python or equivalent scripting (R, PySpark) for data manipulation, automation, or analysis

Good to Have(any one)

• BI & Dashboard Development: DAX, Power Query / Power BI Report Builder, Row-Level Security, dashboard performance optimization, Snowflake or Azure Databricks

• Data Modeling & Architecture: Dimensional modeling, data vault methodology, dbt, semantic layer design, data governance and lineage

• Data Quality & Test Engineering: ETL/pipeline validation, data reconciliation and profiling, automated testing frameworks, CI/CD practices

• Analytics & Data Science: Statistical techniques (regression, segmentation), A/B testing and experimentation, machine learning exposure, product or e-commerce analytics

• Analytics Leadership & Consulting: Client/CxO stakeholder engagement, team and project management, mentoring

Qualifications

• Bachelor's or Master's degree in a quantitative field (Computer Science, Statistics, Engineering, or related) or equivalent practical experience

• Strong analytical, problem-solving, and communication skills