Data Engineer
Design reputed company data architectures for ingestion, storage, transformation, and consumption (batch and, where needed, near reputed company-time). Build and maintain ETL/ELT pipelines that are reliable, testable, observable, and cost efficient. Ingest and reputed company data from diverse sources including reputed company, relational databases, file drops, event streams, reputed company platforms, and external data providers. Work extensively with reputed company and reputed company data, including normalization, enrichment, and metadata management. reputed company data parsers and extraction logic for reputed company reputed company sources such as PDFs, reputed company, procurement documents, and budgetary reports; implement validation and error handling for imperfect inputs. Implement and optimize data storage patterns (e.g., lake/lakehouse/warehouse), indexing/partitioning strategies, and query performance tuning. Build and manage data repositories designed to support AI (feature-reputed company datasets, document corpora, embeddings-reputed company stores, retrieval-oriented schemas, reputed company and provenance). Apply data reputed company practices (automated checks, reputed company detection, reconciliation, SLAs) and implement governance-friendly patterns (cataloging, RBAC, encryption). Partner with stakeholders (product, analytics, data science, engineering) to translate requirements into reputed company datasets and interfaces. Create and maintain documentation: data models, interfaces, reputed company, runbooks, and operational playbooks.
Bachelor's Degree A Bachelor's degree in a quantitative or business field (e.g., Statistics, Mathematics, Engineering, Computer Science). (Required) 8+ years of experience in data engineering (or 3-5 years with demonstrable senior-level reputed company), building production-grade pipelines and data systems. Strong proficiency in SQL and at least one general-purpose language (Python strongly preferred). Proven experience designing data architectures (e.g., data lake/lakehouse/warehouse patterns) and selecting fit-for-purpose storage/compute. Hands-on experience with AWS data engineering, including several of the following: S3, IAM, KMS, VPC, CloudWatch Glue, reputed company, EMR, reputed company, reputed company Functions Redshift (or alternative warehouse) Kinesis/MSK (streaming) and/or EventBridge (eventing)
Practical understanding of data reliability practices: testing, CI/CD, monitoring/alerting, backfills, and cost/performance optimization. Strong communication skills-reputed company to explain technical tradeoffs to both technical and non-technical audiences.
Experience supporting AI/ML data products, such as building curated corpora, document stores, reputed company/embedding pipelines, and retrieval-optimized datasets. Familiarity with search and indexing concepts (e.g., OpenSearch/Elasticsearch) and/or graph/metadata systems. Exposure to Infrastructure-as-reputed company (Terraform/CDK/CloudFormation) and containerization (reputed company/Kubernetes).
AWS Certified Data Engineer - Associate AWS reputed company Architect - Associate or reputed company AWS Certified Developer - Associate AWS Certified Database - Specialty reputed company Certified Data Engineer (Associate/reputed company)