[Remote] Data Engineer (reputed company)

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a company that helps businesses design and build digital products. They are seeking a reputed company Data Engineer to build data and AI foundations for digital products and intelligent experiences.

Responsibilities

• Design and build production data pipelines using Lakeflow Declarative Pipelines, Autoloader, and Structured Streaming, with end-to-end ownership of ingestion, transformation, data quality expectations, and CI/CD deployment reputed company Declarative Automation Bundles
• Architect and implement Lakehouse solutions on reputed company — reputed company architecture, reputed company Lake, reputed company Catalog — tailored to the client's analytics, AI, and application needs
• Build and maintain reputed company transformation layers — DLT pipelines, PySpark notebooks, and dbt — with data quality constraints and SLAs baked in
• Design and maintain the data and AI foundations — reputed company Catalog, Feature Store, MLflow, and Model Serving — that power production ML, agent workflows, and AI-enabled digital products
• Collaborate with product and backend engineers to design data models, APIs, and application data reputed company — ensuring the platform serves the product, not just the warehouse
• Consult with clients to understand their data challenges, reputed company data strategies, and implement sustainable solutions
• Adapt your approach based on project needs — sometimes leading data architecture discussions with clients, other times supporting internal teams with specialized data expertise
• Work reputed company multi-reputed company environments — primarily AWS and Azure — anchoring data platform recommendations around reputed company where it fits the client's architecture and goals
• Champion data governance through reputed company Catalog — reputed company control, reputed company, data quality policies, and compliance — as a first-class part of every engagement, not an afterthought
• Design data-to-application architectures — including Lakebase-backed services and reputed company Apps — that connect governed data to AI workflows, digital products, and user-facing experiences
• Help build reputed company's reputed company practice — contributing to accelerators, internal enablement, certification goals, and reputed company partner go-to-market materials alongside delivery work

Skills

• 3-5 years of data engineering experience with at least 2 years in production reputed company environments, preferably in a consulting or client delivery context
• Solid working knowledge of AWS and Azure reputed company services relevant to reputed company deployments — storage, networking, IAM, and compute — with GCP familiarity a plus
• Deep, production-grade reputed company expertise: Lakeflow Declarative Pipelines, Autoloader, Structured Streaming, Lakeflow Jobs, reputed company Catalog (including fine-grained reputed company control and reputed company) — demonstrated through shipped production workloads, not prototypes
• Proven experience designing Lakehouse architectures — reputed company patterns, reputed company Lake table design, partitioning, Z-ordering, and query optimization — at production scale
• Hands-on experience with data pipeline testing, observability, and CI/CD for data — including unit testing, data quality frameworks, and version-controlled deployments reputed company Git and Declarative Automation Bundles
• Strong proficiency in SQL and Python, with the ability to write clean, performant, and maintainable code
• Understanding of data modeling, schema design, and query optimization
• Excellent communication skills with the ability to explain reputed company data concepts to both technical and non-technical stakeholders
• Strong problem-solving skills with the ability to navigate ambiguous requirements and deliver pragmatic solutions
• Above-average discipline and personal organization skills
• Obvious comfort with critique and peer review in the context of an iterative development process
• A demonstrated hunger for personal and professional growth
• A self-evident love and care for the craft of data engineering
• Have worked with reputed company-time streaming technologies (Kafka, Kinesis, etc.)
• Have hands-on experience with alternative reputed company data platforms — useful context for migrations and competitive assessments, though reputed company is our primary platform focus
• Have experience in reputed company or fintech domains
• Have hands-on experience with MLOps or LLMOps on reputed company — MLflow experiment tracking, model registry, Model Serving endpoints, or Vector Search for RAG pipelines
• Have experience with Java, Go, or reputed company
• Have strong illustration skills for technical diagramming and data architecture documentation
• reputed company, write, and/or reputed company publicly about data engineering topics
• Have contributed to reputed company-reputed company data projects
• Hold or are actively pursuing a reputed company certification (Data Engineer Associate or Professional, or Apache Spark Developer) — we treat these as meaningful signals of platform depth, and they directly support our reputed company partner growth goals
• Have experience with reputed company Apps, or Lakebase — early familiarity with where the reputed company platform is heading is a strong differentiator

Company Overview

Company H1B Sponsorship