Data Engineer Remote

NuView

6d•Remote

About The Position

At NuView Analytics, we help companies accelerate the time to insights from their data. We do this in three ways: data analytics, data diligence, and fractional data science. Our clients are growth-stage companies looking to drive additional value from the data they are sitting on. Through our values of humility, intellectual rigor, and stewardship, we help companies gain a new perspective on their business through their data. The Role We're looking for a Data Engineer to join our growing team and help clients build scalable, reliable data infrastructure. You'll work across the modern data stack, designing pipelines, architecting warehouses, and enabling the analytical layer that our clients depend on. This is a high-impact, client-facing role that combines deep technical execution with strategic thinking.

Requirements

Bachelor's Degree in Computer Science, Engineering, Mathematics, or a related field
2–5+ years of relevant data engineering or software engineering experience
SQL Expert: complex query authoring, query optimization, stored procedures
Python Required: pipeline scripting, automation, data processing
Transformation Tools: dbt required; Spark experience a plus
Ingestion Tools: Fivetran, Airbyte, Rivery, Microsoft Fabric Data Factory, or similar
Orchestration: Airflow, Prefect, Azure Data Factory, Microsoft Fabric, or equivalent
Cloud Platforms: Azure (preferred), AWS, or GCP experience
Data Warehouses: Snowflake, BigQuery, Redshift, Microsoft Fabric, Azure Synapse, or equivalent
Version Control: Git required; branching strategies, pull requests, and code review workflows
Strong communication skills with the ability to translate technical concepts for non-technical stakeholders
Self-starter who thrives in a remote environment and can manage multiple client workstreams
Player-coach mindset: capable of leading projects while growing junior teammates
Intellectually curious about evolving data tooling, architecture patterns, and AI-augmented engineering

Responsibilities

Design, build, and maintain scalable data pipelines for clients across industries
Architect and optimize cloud data warehouse solutions, adapting to each client's stack, which may include Snowflake, BigQuery, Redshift, Microsoft Fabric, or similar platforms
Lead data integration projects from source system to analytical layer, including scoping, delivery, and handoff
Work fluidly across a range of modern data tools and platforms as client engagements demand, picking up new technologies quickly and applying best practices regardless of the toolset
Collaborate with analysts and data scientists to ensure data is clean, reliable, and well-modeled
Champion data quality, testing, and observability best practices across client engagements
Produce and maintain clear technical documentation including pipeline architecture, data dictionaries, lineage maps, and runbooks so clients can understand and own their infrastructure long-term
Document engineering decisions, standards, and workflows in a way that supports knowledge transfer to both clients and junior team members
Research and evaluate new technologies and advocate for tooling investments that benefit the firm
Train and mentor junior team members on engineering standards, pipeline design, and best practices
Participate in client-facing communication, including requirements gathering and progress updates
Flex support when capacity allows: contribute to analyst-side deliverables such as Power BI dashboard development, ad-hoc reporting, or data visualization. We're a lean team and value versatility