Business Intelligence Analyst, Data Engineer

DeepSource GmbH

. Design, build, and maintain ETL/ELT pipelines integrating CRM, ERP, project management tools, spreadsheets, and APIs into centralized data warehouses or data marts .

Posted 10/27/2026full-timeRemote • Ireland, Czechia, Slovenia, Slovakia, Croatia, PolandMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining ETL/ELT pipelines, ensuring data quality and integrity, and optimizing data models for performance. Proficient in utilizing BI tools for reporting and analysis while collaborating effectively with cross-functional teams.

Highest-signal resume keywords

ETL/ELT Pipeline DevelopmentStrong SQL SkillsData Modeling ConceptsBI/Visualization Tool ExperienceCloud Data Warehouse Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ETL/ELT Pipeline DevelopmentSQLData ModelingData Quality AssuranceData AnalysisData IntegrationAutomationAI/LLM Tool IntegrationDashboard DevelopmentData Governance

Soft Skills

Excellent Communication SkillsAnalytical MindsetCollaboration

Tools & Technologies

TableauPower BIFivetranDbtAirflowSnowflakeBigQueryRedshiftWorkatoZapier

Industry Keywords

CRM SystemsERP SystemsOperational Data FlowsData LineagePrompt EngineeringRetrieval-Augmented GenerationAgent-Based ArchitecturesProfessional Services AnalyticsFinance AnalyticsOperations Analytics

Tech Stack

Tools & technologies

AirflowAmazon RedshiftBigQueryCloudERPETLPythonSnowflakeSQLTableau

About the role

Key responsibilities & impact

Design, build, and maintain ETL/ELT pipelines integrating CRM, ERP, project management tools, spreadsheets, and APIs into centralized data warehouses or data marts
Ensure data quality, consistency, and integrity through validation, testing, and monitoring
Optimize star/snowflake data models for reporting performance
Automate manual data processes and reduce reliance on ad hoc spreadsheets
Manage data source connections, credentials, and refresh schedules
Troubleshoot data pipeline failures, latency issues, and discrepancies
Build and maintain Tableau, Power BI, or similar dashboards and reports
Gather reporting requirements from stakeholders and translate them into technical specifications
Define and maintain a single source of truth for key business metrics
Conduct ad hoc analysis supporting business questions and strategic decisions
Monitor dashboard usage and improve reports based on stakeholder feedback
Document data lineage, business logic, and calculation methodology
Design data structures suitable for AI agents and natural-language query tools
Build or support AI-powered reporting assistants and chatbots
Evaluate and integrate LLM-based analytics tools
Establish guardrails for AI-generated analysis and validate trustworthy outputs
Stay current on AI/BI tooling and recommend automation opportunities
Collaborate with Sales, Finance, Operations, Professional Services, IT, and engineering stakeholders
Support rollout of new tools, data sources, and automation initiatives

Requirements

What you’ll need

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: Experience with Python or another scripting language for data manipulation and automation
Preferred: Familiarity with CRM/ERP systems (Salesforce, NetSuite) and operational data flows
Preferred: Experience with API integrations and workflow automation platforms (Workato, Zapier, or similar)
Preferred: Hands-on experience building or integrating AI/LLM-powered tools (Claude, ChatGPT, Copilot) into data workflows
Preferred: Familiarity with prompt engineering, retrieval-augmented generation (RAG), or agent-based architectures for analytics
Preferred: Experience establishing data governance practices suitable for human and AI consumers
Preferred: Prior experience in Professional Services, Finance, or Operations analytics