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Popular data-engineer title and broad skillset increase competition, but seniority and non-FAANG brand temper it.
Data engineering skills are transferable across industries but require strong domain-specific tooling and senior experience.
Explicit 10+ years plus required tech leadership and specific tech experience makes shortlisting strict.
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Lead technical direction for a major product domain or platform capability, aligning with business and customer needs.
Design and maintain advanced data pipelines supporting AI systems (RAG ingestion, embeddings, vector stores) alongside traditional reporting.
Reduce architectural debt, mentor engineering teams, guide multi-quarter roadmaps, and represent Mitratech’s technical expertise externally.
10+ years in software engineering with technical leadership and architecture focus.
Strong expertise in data engineering: data modeling, warehousing, governance, SQL, PostgreSQL, ETL/ELT pipelines, BI and analytics.
Comfortable using AI coding assistants (e.g., Claude Code, Copilot, Cursor) regularly and experienced with AI/LLM-adjacent pipelines.
5+ years experience in Ruby on Rails, React, and modern cloud platforms like AWS.
Experienced in leading cross-functional technical initiatives involving product, engineering, analytics, and business teams.
Skilled in driving innovation in data infrastructure catering to both AI-driven products and traditional BI needs.
Capable of elevating engineering excellence through mentorship, RFCs, knowledge sharing, and external technical representation.