Exadel
Technology
LeadDataEngineer
Neural analysis suggests this role is
optimal for Lead candidates.
“Lead Data Engineer at Exadel. Skills: Data Engineering, ETL/ELT, Cloud Data Services, API Integration. Review data sources. Review access patterns”
Industry & Context.
Identify risks; Identify blockers; Identify dependencies; Identify assumptions
What They're Looking For.
Must Have
Hands-on data engineering background, Hands-on backend engineering background, Experience with ETL/ELT, Experience with data pipelines, Experience with APIs, Experience with cloud data services, Experience with enterprise integrations, Ability to assess data readiness, Ability to assess implementation feasibility, Experience supporting architecture phases, Experience supporting discovery phases, Ability to communicate technical risks clearly
Nice to Have
ERP integration experience, CRM integration experience, MES integration experience, Finance systems integration experience, Reporting systems integration experience, Operational systems integration experience, Experience with data quality, Experience with master data, Experience with data ingestion, Experience with platform modernization, Exposure to AI/ML implementation, Exposure to GenAI implementation
What You'll Do.
Review access patterns
Review integration options
Assess data availability
Assess data completeness
Assess data readiness
Identify ingestion requirements
Identify ETL/ELT requirements
Identify API requirements
Identify system integration requirements
Validate AI use cases
Validate automation use cases
Validate reporting use cases
Identify implementation risks
Identify dependencies
Support platform recommendation
Distinguish pilot scope
Support technical documentation
How You'll Work.
Team & Collaboration
Cross-functional teams; Enterprise leaders
Communication Scope
Technical risk communication
Full Job Description
Why Join Exadel We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next. What powers it all? Our people are ambitious, collaborative, and constantly evolving. What You’ll Do Review available data sources, access patterns, interfaces, and integration options Assess data availability, quality, completeness, and readiness for prioritized use cases Identify ingestion, ETL/ELT, API, and system integration requirements Validate whether proposed AI, automation, and reporting use cases are technically feasible Identify implementation risks, blockers, dependencies, and assumptions Support platform recommendation with implementation-level input Provide rough sizing for Phase 2 build activities Help distinguish what can be piloted quickly versus what requires deeper platform work Support technical documentation for final recommendations What You Bring Strong hands-on data engineering or backend engineering background Experience with ETL/ELT, data pipelines, APIs, cloud data services, and enterprise integrations Working knowledge of Azure, Databricks, Microsoft Fabric, AWS, or comparable platforms Ability to assess data readiness and implementation feasibility Experience supporting architecture and discovery phases Ability to communicate technical risks clearly to non-technical stakeholders Nice to Have ERP, CRM, MES, finance, reporting, or operational systems integration Experience with data quality, master data, data ingestion, and platform modernization Exposure to AI/ML or GenAI implementation prerequisites English level Upper-Intermediate Legal & Hiring Information Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more Reasonable
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