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Senior Data Engineer
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IvoryCloud
Rockville, MD (In Person)
$177,500 Salary, Full-Time
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Job Description
Senior Data Engineer IvoryCloud Rockville, MD Job Details Full-time $155,000 - $200,000 a year 1 day ago Benefits Health insurance 401(k) Paid time off Vision insurance Qualifications Data model design Data quality checks Commercial use (data warehousing systems) Databricks Data Integration (Data management) SQL databases Cloud data warehouses ETL pipeline development Bachelor of Science Data quality assurance Spark Schema design SQL Data Architecture Design (Architecture design skills) Production systems Cloud security best practices implementation ETL process automation Bachelor's degree Data quality monitoring Data Security (Data management) DevOps automation Technical architecture Python Data analytics technologies Full Job Description Job Overview We are seeking a highly capable Senior Data Engineer to design, build, and optimize modern data pipelines and analytics platforms. This role is focused on leveraging Databricks as a development environment for large-scale data engineering, transformation, and analytics workloads—not platform administration. In support of a Department of Energy client, you will work closely with business stakeholders, analytics teams, software engineers, and AI/ML practitioners to build reliable, scalable, and high-performance data solutions that support reporting, operational intelligence, and advanced analytics initiatives. Requirements U.S. Citizenship is required and non-negotiable 2 days a week in the Rockville, MD office are required and non-negotiable. Ability to pass multiple background and employment checks - federal and local. Bachelor's degree Technology, Business, or Related Field Key Responsibilities Design, develop, and maintain scalable data pipelines using Azure Databricks and Apache Spark. Build and optimize batch and streaming data processing solutions. Develop robust ETL/ELT frameworks for structured and semi‑structured data from SQL, APIs, SaaS apps, and Data Live Lake Storage. Implement transformation logic using PySpark, SQL, and Delta Lake within a Lakehouse / Medallion architecture. Integrate and model data from SQL, SaaS systems, and cloud storage into unified, analytics‑ready and AI‑ready structures. Partner with analytics, BI, and AI/ML teams to deliver trusted datasets, semantic layers, and AI‑ready data (features, vector‑ready patterns, embeddings). Improve data quality, observability, lineage, governance, and security in alignment with Azure and enterprise standards. Optimize data performance, storage costs, and processing efficiency in cloud environments. Participate in architecture discussions and contribute to the evolution of the organization's data platform and engineering best practices. Required Qualifications 5+ years of hands‑on data engineering experience (or equivalent depth), including production‑grade pipelines. Strong experience building solutions using Databricks, Spark/PySpark, SQL, and Delta Lake. Solid understanding of Lakehouse and Medallion architectures and when to apply them. Advanced SQL skills and experience supporting analytics, BI, or operational reporting workloads. Experience developing and operating ETL/ELT pipelines on Azure or another major cloud platform. Familiarity with Git‑based development and CI/CD practices for data pipelines (Azure DevOps or GitHub preferred). Strong understanding of data modeling (relational + dimensional) for both operational and analytical workloads. Working knowledge of data quality, lineage, governance, and security concepts in cloud environments.