# Business Intelligence Analyst & Data Engineer- Remote

**Company:** [DeepSource Technologies](https://jobs.workable.com/companies/bSz5yPYQuy7zGF2AaBwdRp.md)
**Location:** Remote
**Workplace:** remote
**Employment type:** Full-time

[Apply for this job](https://jobs.workable.com/view/ab05d78f-0921-46f1-8aca-d3745353a34a)

## Description

We're looking for a hybrid **Business Intelligence Analyst & Data Engineer** who can operate across the full data lifecycle — from building and maintaining reliable data pipelines to designing dashboards and reports that drive business decisions. This role sits at the intersection of data infrastructure and analytics: you'll own how data flows into our systems and how it's ultimately consumed by stakeholders across the organization.

This is a great fit for someone who enjoys both the technical rigor of data engineering and the storytelling/analytical side of BI work, and who wants ownership over an end-to-end data product rather than sitting in just one lane. AI-driven analytics is a growing part of our roadmap, so we're especially interested in candidates who are curious about applying AI/LLM tools to make data more accessible and self-service across the business.

**Key Responsibilities**

**Data Engineering**

-   Design, build, and maintain ETL/ELT pipelines that integrate data from multiple source systems (CRM, ERP, project management tools, spreadsheets, APIs) into centralized data warehouses or data marts
-   Ensure data quality, consistency, and integrity across pipelines through validation, testing, and monitoring
-   Optimize data models (star/snowflake schemas) for reporting performance
-   Automate manual data processes and reduce reliance on ad hoc spreadsheet work
-   Manage data source connections, credentials, and refresh schedules
-   Troubleshoot and resolve data pipeline failures, latency issues, and discrepancies

**Business Intelligence & Analytics**

-   Build and maintain dashboards and reports (e.g., in Tableau, Power BI, or similar) that translate raw data into clear, actionable insights
-   Partner with business stakeholders to gather reporting requirements and translate them into technical specifications
-   Define and maintain a single source of truth for key business metrics (a data dictionary / metrics glossary)
-   Conduct ad hoc analysis to answer business questions and support strategic decision-making
-   Monitor dashboard usage and proactively improve reports based on stakeholder feedback
-   Document data lineage, business logic, and calculation methodology for transparency and auditability

**AI-Enabled Analytics**

-   Design and maintain data structures (clean schemas, semantic layers, metric definitions) that are well-suited for consumption by AI agents and natural-language query tools, not just human-facing dashboards
-   Build or support AI-powered reporting assistants/chatbots that let stakeholders ask business questions in plain language and get accurate, governed answers
-   Evaluate and integrate LLM-based tools into the analytics stack (e.g., automated insight generation, anomaly detection, natural-language-to-SQL interfaces)
-   Establish guardrails for AI-generated analysis — certified data sources, citation of underlying data, and validation processes to ensure trustworthy outputs
-   Stay current on AI/BI tooling trends and proactively recommend where automation or AI can reduce manual reporting work

**Cross-Functional Collaboration**

-   Work closely with department leaders (Sales, Finance, Operations, Professional Services, etc.) to understand data needs and pain points
-   Act as a technical liaison between business teams and IT/engineering on data-related initiatives
-   Support the rollout of new tools, data sources, or automation initiatives (e.g., AI-powered reporting agents, workflow automation platforms)

## Requirements

-   Bachelor's degree in Computer Science, Data Science, Information Systems, Statistics, or a related field (or equivalent practical experience)
-   3+ years of experience in a data engineering, BI analyst, or analytics engineering role
-   Strong SQL skills, including experience writing complex queries, optimizing performance, and working with large datasets
-   Experience building and maintaining ETL/ELT pipelines (custom scripts, or tools like Fivetran, dbt, Airflow, Workato, or similar)
-   Hands-on experience with a BI/visualization tool (Tableau, Power BI, Looker, or similar)
-   Solid understanding of data modeling concepts (dimensional modeling, normalization, star schemas)
-   Experience working with cloud data warehouses (Snowflake, BigQuery, Redshift, or similar)
-   Strong analytical mindset with the ability to translate ambiguous business questions into structured data analysis
-   Excellent communication skills — able to explain technical concepts to non-technical stakeholders

**Preferred Qualifications**

-   Experience with Python or another scripting language for data manipulation and automation
-   Familiarity with CRM/ERP systems (Salesforce, NetSuite) and how operational data flows from them
-   Experience with API integrations and workflow automation platforms (Workato, Zapier, or similar)
-   Hands-on experience building or integrating AI/LLM-powered tools (e.g., Claude, ChatGPT, Copilot) into data workflows — such as natural-language querying, automated report generation, or AI-driven data agents
-   Familiarity with prompt engineering, retrieval-augmented generation (RAG), or agent-based architectures as applied to analytics
-   Experience establishing data governance practices (certified data sources, metric definitions, documentation standards) suitable for both human and AI consumers
-   Prior experience in a Professional Services, Finance, or Operations analytics function