Senior Data Engineer

Node.Digital; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical

Dental

Vision

Life Insurance

HSA

401K matching

PTO/Sick

Holidays

Online Training

Job summary

Node.Digital is seeking a Senior Data Engineer in Herndon, VA with remote work options. You will design, build, and maintain scalable data architectures and pipelines using Azure Synapse, Azure ML, and Parquet formats to support SBA OIG investigations and audits.

You will ensure data quality, implement source control, and collaborate on analytics tooling, while staying current with emerging AI-assisted data engineering capabilities and industry best practices.

Qualifications

• Bachelor’s degree in data engineering, CS, data science, ML, math or related field; or 5 years of applied work experience.
• 5 years maintaining SQL databases and advanced operations in SQL/T-SQL.
• 3 years working with Azure Synapse and Azure ML in modern data stack.
• 3 years manipulating data in Python; Pandas required; PySpark/Polars preferred.

Responsibilities

• Provide authoritative expertise on data engineering methods and pipeline design.
• Design, implement, and maintain data architecture and assets under source control.
• Develop ELT and ETL pipelines in Azure Synapse and Azure ML (SDK v1 & v2).
• Migrate source data into Azure Data Lake Storage.
• Normalize entity attributes (addresses, phones, etc.).
• Review and improve architecture, addressing bottlenecks and drift.
• Establish quality controls, error handling, logging, and validation across pipelines.
• Incorporate source control across pipelines and analytics codebases.
• Optimize ingestion, processing, and storage across diverse datasets.
• Develop self-service analytics for SBA OIG analysts.
• Author SOPs for data pipelines and Azure deployments.
• Produce data architecture documentation and data dictionaries.
• Expand environment with new datasets/services per intake/testing process.
• Stay current with AI tooling relevant to data engineering.

Skills

SQL

Python

Pandas

PySpark

Polars

Data modeling

ETL/ELT pipelines

Azure data services

Source control

CI/CD

Education

Bachelor’s degree in data engineering, CS, data science, ML, math

5 years of relevant work experience

Tools

Azure Synapse

Azure Machine Learning

Azure Data Lake Storage

Parquet

Git

Terraform

Bicep

Python SDK

CLI

REST APIs

Job description

Senior Data Engineer

Location: Herndon, VA (Remote Work)

Must have an Public Trust Clearance

KEY RESPONSIBILITIES

• Provide authoritative expertise on data engineering methods and best practices, including code first development approaches and modern pipeline design patterns.
• Design, implement, and maintain the data architecture that supports products and end users, with all assets managed under source control.
• Design, implement, and maintain ELT and ETL pipelines for efficient processing of source data in Azure Synapse and Azure Machine Learning, using both SDK V1 and SDK V2.
• Migrate source data identified by SBA OIG into Azure Data Lake Storage.
• Normalize entity attributes such as addresses, phone numbers, and other common fields.
• Review, maintain, and improve existing architecture and pipelines, including periodic audits addressing bottlenecks, deprecated dependencies, and architecture drift.
• Establish quality controls across all pipelines and introduce error handling, logging mechanisms, and validation checks.
• Incorporate source control across all pipelines and analytics codebases so code can evolve iteratively without destabilizing the architecture.
• Optimize ingestion, processing, and storage across a wide variety of datasets and data types, including modern columnar formats such as Parquet.
• Develop self service capabilities that let SBA OIG analysts query and export data for investigations and audits.
• Author robust standard operating procedures governing the authoring, development, validation, publishing, execution, and monitoring of all data pipelines and assets in the Azure environment.
• Produce detailed documentation of the data architecture, including data dictionaries, entity relationship diagrams, and pipeline process maps.
• Maintain and expand the environment with additional datasets and services on request, following a defined intake and testing process before production deployment.
• Stay current with emerging AI tooling relevant to data engineering and contribute to exploratory work evaluating automation and language model assisted capabilities.

Education

Bachelor’s degree in data engineering, computer science, data science, machine learning, mathematics, or a related field. Alternatively, five years of applied work experience in any of the same fields.

• 5 years - Maintaining SQL databases and conducting advanced operations in SQL and T-SQL.
• 5 years - Designing, implementing, and maintaining ELT and ETL processes in cloud based data analytics environments.
• 3 years - Working in Azure Synapse and Azure Machine Learning with the modern data stack. Certifications preferred, DP-203 or equivalent.
• 3 years -Manipulating data in Python. Pandas is required. PySpark and Polars preferred. Experience developing reusable, modular code preferred.

PREFERRED QUALIFICATIONS

• DP-203, Microsoft Certified Azure Data Engineer Associate, or an equivalent current certification.
• Implementing pipelines and infrastructure using code first approaches: Python SDK, CLI, REST APIs, or infrastructure as code tooling such as Terraform or Bicep.
• Implementing source control and continuous integration and delivery workflows for data assets.
• Demonstrated familiarity with AI coding assistants and large language model integration patterns.
• PySpark or Polars at production scale.
• Entity resolution and attribute normalization across records with inconsistent addresses, names, and identifiers.
• Building self service analytic access for non engineering users.

We are proud to offer competitive compensation and benefits packages to include

• Medical
• Dental
• Vision
• Basic Life
• Health Saving Account
• 401K matching
• Three weeks of PTO/Sick
• 11 Paid Holidays
• Pre-Approved Online Training