Senior Data Engineer

Job not on LinkedIn

🕒 September 11

🇺🇸 United States – Remote

💵 $115k - $160k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 29%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Imagine Believe Realize, LLC.

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2007

🏛️ Government

🔒 Cybersecurity

Government • Cybersecurity

Imagine Believe Realize, LLC is a software and systems engineering services company founded in 2007 that provides technical solutions to public and private sector clients. IBR specializes in software engineering (Agile/Scrum, N-tier designs, enterprise SDLC leadership), systems engineering (TOGAF, DoDAF, enterprise architecture), cloud computing, cybersecurity (assessments, DevSecOps, vCISO, incident response, CMMC certified), identity, credential and access management (ICAM) for DoD and federal customers, mobility solutions (BYOD, mobile development), Salesforce customization, Geographic Information Systems (GIS) software for the U. S. Census Bureau, and performance/scaling for high-performance computing environments. It holds government contract vehicles and certifications and positions itself as a mission-focused contractor serving federal clients including DoD, Navy, and the U. S. Census Bureau.

📋 Description

• Design and implement secure, next-generation data engineering solutions supporting critical missions • Collaborate with technical leaders, business stakeholders, and multidisciplinary teams • Support implementation of the DON MAHRS program Data Strategy and High-Level Total Force Data Hub implementation plan • Develop, implement, integrate, and sustain data architectures, data hubs, data lakes, and data warehouses • Design and develop data models, data structures, and data acquisition processes • Develop engineering and implementation plans for data hubs, acquisition, modeling, integration, and related activities • Research and evaluate enterprise data sources to identify authoritative and reliable sources • Plan, create, and maintain data architectures aligned with business requirements • Design, develop, maintain, and optimize ETL/ELT pipelines and transformation processes • Develop and maintain batch and streaming pipelines using Spark, Python, Databricks, Palantir Foundry, Kafka, and related tools • Develop data acquisition processes to ingest, transform, validate, and integrate diverse enterprise data • Implement incremental loading strategies and address late-arriving data, processing windows, freshness, and lifecycle considerations • Automate manual data processes and improve workflow efficiency, reliability, and scalability • Develop, maintain, and optimize solutions within Databricks and enterprise data lake environments • Configure, monitor, and manage Databricks clusters according to DON policies and security requirements • Document Databricks cluster configurations, parameters, and operational standards • Develop and maintain Spark-based processing solutions using PySpark, Spark SQL, DataFrames, and Data Sets • Implement and maintain Delta Lake and, where applicable, Delta Live Tables solutions • Optimize data processing, storage, and query performance • Support Palantir Foundry ontologies, ETL/ELT pipelines, applications, interfaces, and enterprise integrations • Develop and maintain Kafka streaming solutions, topics, Schema Registry, Kafka Streams, and ksqlDB components • Develop Python data-processing applications and AWS Lambda functions • Support processing with AWS S3, Kinesis, Lambda, and DynamoDB • Monitor, troubleshoot, and optimize cloud-based data-processing solutions • Develop data-quality controls, validation processes, and quality gates • Develop and execute data-driven and unit testing for Spark, Python, and other processing solutions • Establish data lifecycle policies covering retention, backup, recovery, and data management • Monitor and troubleshoot pipelines and processing jobs • Identify improvements to data-processing performance, reliability, scalability, and maintainability

🎯 Requirements

• 5+ years of professional data engineering-related experience • 5+ years of IT experience focusing on enterprise data engineering, including data modeling, data quality, data mapping tools, and technical documentation • Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or an IT-related field required • Must be eligible to obtain and maintain a Secret security clearance • United States Citizenship required for eligibility to obtain a Secret security clearance • Must reside in the continental United States • Professional experience in data architecture, data engineering, data hub, data lake, and/or data warehouse development • Experience designing, developing, implementing, and supporting enterprise-scale data engineering solutions • Experience with data modeling, data mapping, data quality, data integration, and data management • Experience supporting large-scale, high-performance enterprise data applications • Experience developing and supporting ETL/ELT data pipelines and data transformation processes • Hands-on experience with Databricks required • Experience with Databricks and/or Palantir Foundry required • Experience with Python and SQL • Experience with Apache Spark and/or PySpark, including Spark SQL, DataFrames, and/or Data Sets preferred • Experience with batch and streaming data processing architectures • Experience with Kafka and/or other distributed streaming technologies • Experience developing and supporting Kafka Streams • Experience working in an AWS cloud environment, including S3, Lambda, Kinesis, and/or DynamoDB • Experience with Git-based version control, including branching, merging, pull requests, and repository management • Experience supporting CI/CD pipelines and cloud monitoring with Jenkins, Docker, and/or CloudWatch preferred • Experience with Palantir Foundry preferred • Experience with the Jupiter data and analytics environment preferred but not required • Active CompTIA Security+ or CompTIA Network+ certification preferred; if selected, must be able to obtain CompTIA Security+ before supporting the program • Ability to debug, troubleshoot, design, and implement solutions to complex technical issues • Ability to thrive in a team-based environment • Experience briefing technology solution benefits and constraints to partners, stakeholders, team members, and senior management • Strong written and verbal communication • Occasional travel to client sites or meetings may be required • Employment contingent upon identity verification and authorization to work in the United States

🏖️ Benefits

• Nationwide medical, dental, and vision insurance • 3 weeks of Paid Time Off • 11 Paid Federal Holidays • 401k matching • Life Insurance at no cost to employees • Short-Term Disability at no cost to employees • Long-Term Disability at no cost to employees • Supplemental insurance options • Flexible spending accounts • Dependent Care spending accounts • Wellness incentives • Reimbursement for professional development and certifications • Training assistance opportunities to support career growth and progression • Hybrid and Remote work opportunities to support work-life balance • Flexible scheduling options • Flexible work arrangements may be available based on business needs

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