Senior Data Engineer Consultant

Accountabilities:
Assess the current data platform, architecture, and engineering practices, identifying technical gaps, risks, and opportunities for improvement while delivering a comprehensive roadmap for modernization. Educate engineering leadership and architects on modern data engineering concepts, covering traditional architectures as well as AI-native approaches through workshops, technical guidance, and knowledge-sharing sessions. Design scalable target-state data platform architectures spanning data ingestion, transformation, storage, orchestration, governance, observability, and serving layers. Develop architectural strategies for PostgreSQL migration, workload optimization, performance, replication, partitioning, and phased migration from existing database environments. Design canonical data models that unify structured and unstructured data across multiple systems through entity resolution, schema harmonization, master data management, and conflict resolution. Define scalable approaches for data residency, multi-region deployments, tenant-aware architectures, regulatory compliance, and secure cross-region data access. Establish enterprise data governance frameworks covering access control, data classification, lineage, retention, auditability, security, privacy, and compliance requirements. Identify and prioritize business use cases that leverage the data platform, including advanced analytics, semantic search, AI-powered insights, compliance monitoring, and customer intelligence. Produce lasting technical documentation, architectural decision records, migration guides, reference materials, and best practices that enable long-term platform success. Provide ongoing architectural advisory support through design reviews, technical consultations, and strategic recommendations throughout the engagement. Requirements 8–10+ years of experience in data engineering, data platform architecture, or enterprise data consulting, with expertise in designing large-scale data ecosystems. Strong consulting or architecture background with demonstrated experience delivering strategic guidance, technical advisory, and knowledge transfer rather than primarily developing production code. Deep expertise in PostgreSQL architecture, database optimization, extensions, replication, partitioning, and SQL Server to PostgreSQL migration strategies. Extensive experience designing canonical data architectures, master data management solutions, entity resolution frameworks, and heterogeneous data integration. Strong understanding of traditional data engineering practices including ETL/ELT, dimensional modeling, change data capture, orchestration, and data quality management. Practical knowledge of AI-native data engineering approaches, including embedding pipelines, semantic search, vector databases, LLM-assisted workflows, and intelligent automation. Experience designing multi-region, multi-tenant, or data residency-compliant architectures with strong knowledge of governance, security, privacy, and regulatory requirements. Familiarity with modern cloud data platforms and technologies such as Python, Azure services, Elasticsearch, orchestration tools, dbt, Airflow, Databricks, Snowflake, or comparable ecosystems is highly desirable. Excellent analytical, communication, and presentation skills with the ability to explain complex architectural concepts to senior technical and business stakeholders. Strong documentation skills with experience creating architecture diagrams, technical standards, migration plans, and reusable reference materials. Experience within financial services, investment management, enterprise SaaS, or regulated industries is advantageous but not required. Benefits Competitive consulting engagement with attractive compensation. Fully remote opportunity based in India. Flexible contract engagement with the possibility of ongoing strategic advisory work. Opportunity to influence the architecture of a global enterprise-scale AI and data platform. Direct collaboration with senior engineering leadership and architecture teams. Exposure to cutting-edge technologies across AI, cloud platforms, modern data engineering, and enterprise architecture. High-impact strategic work focused on long-term platform transformation rather than routine implementation. Collaborative, fast-paced environment that values technical excellence, innovation, and knowledge sharing.

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