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Lead Data Engineer We are seeking a Lead Data Engineer to build a modern analytics ecosystem for the organization. This is a highly visible, greenfield role that requires deep technical expertise, strong architectural instincts, and the ability to operate independently in an emerging environment. You will design and implement the full data platform — including orchestration, ingestion, modeling, warehousing, and BI layers — while collaborating closely with product and business stakeholders. This role is ideal for someone who thrives in ambiguity, loves building from scratch, and brings a high standard of technical excellence. Key Responsibilities Platform Architecture & Engineering Lead architecture and foundational design for a new analytics ecosystem Build cloud-based data warehouses or lakehouses using Databricks or similar technologies Design scalable ETL/ELT pipelines, orchestration layers, and transformation frameworks Establish best practices across data modeling, quality, lineage, and governance Define engineering standards and deployment patterns for long-term scalability Build robust ingestion frameworks, structured and unstructured data pipelines, and transformation layers Develop curated data models that support self-service analytics and BI capabilities Implement automation, monitoring, and testing patterns for reliable data delivery Partner with engineers, analysts, and business teams to translate requirements into high-quality data products Analytics & BI Enablement Build analytical and BI experiences end-to-end using tools such as Zoho, Qlik, or similar platforms Enable scalable self-service analytics workflows and governed data access Support dashboard development, semantic layers, and metrics definitions Drive adoption of modern analytics tooling and standards across the business Provide technical leadership in a small, senior-level team Operate effectively in high-ambiguity environments, driving clarity and structure Collaborate closely with product, engineering, and business stakeholders Document architecture, data flows, and platform standards Qualifications Required Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field 8+ years in data engineering, BI platform engineering, analytics engineering, or similar roles Proven experience building data platforms or warehouses from the ground up Strong hands‑on expertise in ETL/ELT, orchestration, and transformation pipelines Advanced experience designing cloud-based data warehouses or lakehouse environments Ability to lead greenfield platform development and make foundational architectural decisions Strong proficiency building analytical/BI experiences end-to-end Ability to collaborate closely with cross‑functional partners and translate needs into scalable solutions Preferred Experience with Databricks , Spark , or comparable lakehouse technologies Familiarity with Zoho , Qlik , or modern BI tools Experience enabling self‑service analytics environments Strong understanding of modern data stack tooling (orchestration, automation, monitoring) Background working in startup‑style, greenfield, or high‑growth teams Relevant certifications (Azure, Databricks, BI tools) About Us We build modern, scalable, and high-quality data platforms that empower teams to make intelligent decisions. By combining strong engineering fundamentals, modern cloud technologies, and thoughtful analytics design, we help organizations transform raw data into meaningful insights. Why Join Us This is a rare opportunity to build an entire analytics ecosystem from scratch. You’ll influence architecture, shape engineering standards, partner closely with business leaders, and own a platform that will scale for years to come. If you want to create, innovate, and lead in a greenfield environment — this is the role for you. Seniority level Mid‑Senior level Employment type Contract Job function Engineering, Information Technology, and Design Industries Software Development, IT System Custom Software Development, and IT Services and IT Consulting #J-18808-Ljbffr