Business Analytics Engineer

Software Finder•201 District, VA

7d•Onsite

About The Position

Software Finder is seeking a skilled and business-oriented Business Analytics Engineer to bridge the gap between business intelligence and analytics engineering. This role will own dashboards and reporting while building the underlying semantic and metrics layer that ensures consistent, reliable KPI definitions across the organization. The ideal candidate combines strong SQL, data modelling, and dashboard-development capabilities with the ability to understand stakeholder needs and translate ambiguous business questions into well-defined analytical solutions.

Requirements

Bachelor’s degree in Data Science, Computer Science, Business Analytics, Statistics, Economics, Information Systems, or a related field.
2–4 years of relevant experience in business intelligence, analytics engineering, data analytics, or a related role.
Advanced SQL skills, including complex joins, CTEs, window functions, aggregations, and query optimization.
Hands-on experience developing dashboards and reports using tools such as Power BI, Tableau, Looker, or a similar BI platform.
Experience with data modelling and building reusable analytical datasets.
Working knowledge of dbt or a similar SQL-based data transformation framework.
Understanding of semantic layers, metrics layers, dimensional modelling, and KPI governance.
Experience identifying, investigating, and reconciling data-quality issues.
Ability to translate business requirements into scalable data models, reports, and dashboards.
Strong analytical thinking, problem-solving, and attention to detail.
Strong stakeholder-management and communication skills.
Familiarity with Git and collaborative development workflows.
Willingness to work onsite in Lahore from 10:00 AM to 7:00 PM PKT.

Nice To Haves

Experience working with cloud data warehouses such as Amazon Redshift, Snowflake, BigQuery, or Databricks.
Familiarity with AWS data and analytics services.
Experience implementing automated data tests, documentation, and lineage using dbt.
Knowledge of dashboard performance tuning and cloud-query cost optimization.
Experience with Python for data validation, automation, or analysis.
Familiarity with data procurement, third-party datasets, APIs, or vendor data management.
Experience creating curated self-service datasets for business teams.
Understanding of data governance, access controls, data privacy, and reporting best practices.
Experience working in a B2B technology, SaaS, marketplace, or data-driven organization.

Responsibilities

Design, build, maintain, and improve dashboards and reports for business stakeholders.
Develop and manage the semantic and metrics layer using dbt models or similar technologies.
Ensure KPIs and business metrics are defined consistently and reused across teams, reports, and dashboards.
Write and optimize complex SQL queries for reporting, data modelling, and ad hoc business analysis.
Gather requirements from stakeholders and translate ambiguous requests into clearly scoped data models, metrics, and reports.
Partner with Data Engineering to identify upstream data-quality issues, reconcile discrepancies, and improve data reliability.
Investigate and resolve mismatches between source systems, models, dashboards, and stakeholder reports.
Maintain clear documentation for KPI definitions, data models, reporting logic, and analytical assumptions.
Establish governance practices that prevent metric definitions from drifting across departments.
Monitor dashboard performance, query execution, data freshness, and associated infrastructure costs.
Optimize models, queries, and dashboards to improve performance and cost efficiency.
Manage day-to-day data procurement activities, including coordinating access to required internal and external data sources.
Prepare clean, curated, and analysis-ready datasets for downstream teams to conduct their own analysis.
Conduct data validation and quality checks before publishing datasets, metrics, or reports.
Support stakeholders in interpreting metrics and using dashboards effectively.
Follow version control, testing, documentation, and review standards for analytics development.
Perform additional business analytics and data-related tasks as assigned.