Senior Data Engineer

Wix

Senior Data Engineer providing expertise on data engineering methods at Integres, LLC. Collaborating with the Office of the Inspector General on data products and processes.

Posted 7/2/2026full-timeRemote • District of Columbia, Washington • 🇺🇸 United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in designing and maintaining ELT/ETL pipelines and data architecture in Azure environments, with a strong focus on SQL, Python, and modern data stack methodologies. Proficient in implementing source control, CI/CD workflows, and quality controls to ensure data integrity and efficiency.

Highest-signal resume keywords

ELT/ETL Pipeline DevelopmentAzure SynapseAzure Machine LearningSQL and T-SQL ProficiencyPython Data Manipulation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Engineering MethodsCode-First DevelopmentData Architecture DesignSQL Database MaintenancePython ProgrammingPandasPySparkCI/CD WorkflowsData Quality ControlsModular Code Development

Tools & Technologies

Azure SynapseAzure Machine LearningPython SDKREST APIsIaC ToolingSource Control SystemsCI/CD ToolsData Analytics CodebasesData DictionariesER Diagrams

Certifications & Qualifications

DP-203

Industry Keywords

Data ProductsData ArchitectureData PipelinesModern Data StackColumnar FormatsData IngestionData ProcessingData StorageAI ToolsAutomation

Tech Stack

Tools & technologies

AzureCloudETLPandasPySparkPythonSQL

About the role

Key responsibilities & impact

Assist TSD with data products by providing highly skilled and authoritative expertise on data engineering methods and best practices, including code-first development approaches and modern pipeline design patterns.
Design, implement, and maintain an efficient, secure, stable, and flexible data architecture that supports products and end-users, with all assets managed via source control.
Design, implement, and maintain ELT/ETL pipelines for efficient processing of source data in Azure Synapse and Azure Machine Learning (using SDK V1 and SDK V2)
Review, maintain, and improve existing architecture and pipelines, including periodic audits to address bottlenecks, deprecated dependencies, and architecture drift.
Establish quality controls for maintaining all pipelines, and introduce error handling, logging mechanisms, and validation checks.
Incorporate source control for all pipelines and data analytics codebases to enable iterative code development while ensuring data architecture stability.
Optimize the ingestion, processing, and storage of a wide variety of datasets and data types, including modern columnar formats such as Parquet.
Develop self-service capabilities for SBA OIG analysts to query and export data for investigations and audits.
Coordinate with data scientists to ensure the architecture efficiently supports machine learning algorithms and data pipelines in Azure Machine Learning.
Develop robust standard operating protocols (SOPs) dictating the authoring, development, validation, publishing, execution, and monitoring of all data pipelines and assets in Azure environment.
Provide detailed documentation of the data architecture, including data dictionaries, ER diagrams, and pipeline process maps.
Maintain and expand the environment with additional datasets and services upon request, following a defined intake and testing process prior to production deployment.
Stay current with emerging AI tools relevant to data engineering and contribute to exploratory efforts evaluating automation and LLM-assisted capabilities.

Requirements

What you’ll need

Five (5) years of hands-on experience in maintaining SQL databases and conducting advanced operations in SQL and T-SQL
Five (5) years of hands-on experience in designing, implementing, and maintaining ELT/ETL processes in cloud-based data analytics environments
Three (3) years of hands-on experience in working in Azure Synapse and Azure Machine Learning, with the modern data stack
Certifications preferred (DP-203 or equivalent)
Manipulating data in Python. Pandas required. PySpark/Polars preferred.
Experience developing reusable, modular code preferred.
Implementing pipelines and infrastructure using code-first approaches (Python SDK, CLI, REST APIs, or IaC tooling)
Implementing source control and CI/CD workflows
Demonstrated familiarity with AI coding assistants and LLM integration patterns

Benefits

Comp & perks

Healthcare and Insurance: medical, dental, vision, short- and long-term disability protection, basic life and AD&D insurance
401(k) Savings Plan
Accrued Paid Time Off (PTO)
Employee Recognition and Rewards
Employee Referral Bonuses