Data Engineer, Databricks

🔥 12 minutes ago

⛰️ Colorado, District of Columbia, +5 more states – Remote

⛰️ Colorado – Remote 🏛️ District of Columbia – Remote 🌽 Illinois – Remote 🗽 New York – Remote 🍂 Massachusetts – Remote 🤠 Texas – Remote ⚔️ Virginia – Remote

💵 $113k - $188k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

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Guidehouse

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 2018

🏥 Healthcare

🎖️ Defense

📦 Logistics

💰 Grant on 2023-02

Healthcare • Defense • Logistics

Guidehouse is a global consultancy offering advisory, digital, and managed services across commercial and public sectors. It is purpose-built to support industries such as national security, financial services, healthcare, energy, and infrastructure. Guidehouse collaborates with leaders to navigate complexity and drives transformational changes that impact the future. Their expertise spans data analytics, digital technologies, risk management, and more, with a strong emphasis on sustainability and innovation.

📋 Description

• Design, build, and maintain scalable data pipelines using Databricks, PySpark, SQL, Delta Lake, and related cloud-native data engineering tools • Develop and support batch and streaming data workflows, including ingestion, transformation, validation, and publishing of curated data products • Write, optimize, and maintain Python, PySpark, and SQL code for data processing, orchestration, and performance tuning • Work with large-scale datasets using Databricks, Spark, Delta Lake, Unity Catalog, and cloud storage services • Troubleshoot and resolve data pipeline failures, performance issues, data quality issues, and workflow bottlenecks • Translate business and technical requirements into data engineering designs, processing scripts, and job orchestration workflows • Perform data validation, quality checks, code reviews, and issue resolution to support accurate and reliable data products • Collaborate with cross-functional teams including solution architects, data scientists, analysts, DevOps engineers, and client stakeholders • Communicate technical concepts, delivery impacts, and data engineering considerations to technical and non-technical audiences • Document pipelines, datasets, data models, workflows, and engineering decisions to support maintainability, transparency, and reuse • Follow data governance, security, lineage, and compliance standards within the Databricks platform

🎯 Requirements

• Bachelor’s degree in computer science, engineering, mathematics, statistics, or another relevant field • 3-8 years of relevant experience in data engineering, data architecture, or cloud data platform implementation • Strong experience with Python, PySpark, and SQL for data transformation, pipeline development, and data processing • Experience with Databricks, Spark, Delta Lake, Unity Catalog, or similar cloud-native data platforms • Experience developing batch or streaming data pipelines, ETL/ELT workflows, and reusable data assets • Experience with data modeling, data warehousing, data quality validation, and large-scale data processing concepts • Ability to troubleshoot technical issues, communicate engineering recommendations clearly, and work effectively in team-based delivery environments • Experience applying data governance, access control, lineage, and security practices within cloud data platforms

🏖️ Benefits

• Comprehensive total rewards package • Competitive compensation • Flexible benefits package