Senior Data Engineer

Node.Digital LLC; Herndon (VA); Hybrid; USD 120,000 - 160,000; Full time

Benefits offered by this job

Medical

Dental

Vision

Basic Life

Health Saving Account

401K matching

Three weeks of PTO/Sick

11 Paid Holidays

Pre-Approved Online Training

Job summary

Node.Digital LLC in Herndon, VA (Remote Work) seeks a Senior Data Engineer with Public Trust Clearance to design and maintain data architectures supporting products and end users. You will manage ELT/ETL pipelines, ensure source control, and optimize Azure-based data workflows for reliable analytics and audits.

The role emphasizes building scalable pipelines, data quality, and self-service access for SBA OIG analysts, with documentation and governance as core objectives.

Qualifications

• 5 years - Maintaining SQL databases and advanced SQL/T-SQL operations.
• 5 years - Designing and maintaining ELT/ETL in cloud data analytics environments.
• 3 years - Working with Azure Synapse and Azure ML in the modern data stack.
• 3 years - Python with Pandas; PySpark and Polars preferred; reusable modular code.

Responsibilities

• Provide expertise on data engineering methods and best practices.
• Design and maintain data architecture with source-controlled assets.
• Build ELT/ETL pipelines in Azure Synapse and Azure ML.
• Migrate data into Azure Data Lake Storage and normalize attributes.
• Establish quality controls across pipelines; implement logging and validation.
• Incorporate source control across pipelines and analytics codebases.
• Optimize ingestion, processing, and storage across diverse datasets.
• Develop self-service analytics access for SBA OIG analysts.
• Produce documentation including data dictionaries and process maps.
• Stay current with AI tooling relevant to data engineering.

Skills

SQL

Python

Azure Synapse

Azure ML

Pandas

PySpark

Polars

Code-first pipelines

Terraform

Education

Bachelor's degree in data engineering

Tools

SQL Server

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