Data Engineer

Job not on LinkedIn

🕒 September 11

🐊 Florida – Remote

🐊 Florida – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 30%

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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Sparibis

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2018

💼 Consulting

🔒 Cybersecurity

🏢 Enterprise

Consulting • Cybersecurity • Enterprise

Sparibis is an Orlando-based IT engineering and consulting firm. It provides program management and project controls support along with SDLC leadership and systems engineering. Its listed capabilities include cyber security engineering, cloud and DevSecOps engineering, mobility/software engineering, CRM and enterprise portals, test and operations engineering, and data management.

📋 Description

• Provide data engineering expertise in developing, implementing, integrating, and sustaining data architectures, data hubs, data lakes, and data warehouse solutions • Support design and development of data models, data structures, and data acquisition processes for data-driven decision-making across the HC/HR Data Domain • Develop engineering and implementation plans for data hubs, data acquisition, data modeling, data integration, and related data engineering activities • Research and evaluate data sources to identify authoritative, reliable, and appropriate sources for data hub development • Plan, create, and maintain data architectures aligned with business requirements • Design, develop, maintain, and optimize ETL/ELT pipelines and data transformation processes • Develop and maintain batch and streaming data pipelines using Spark, Python, Databricks, Palantir Foundry, Kafka, and related tools • Develop and maintain data acquisition processes to ingest, transform, validate, and integrate enterprise data • Implement incremental loading strategies and address late-arriving data, processing windows, data freshness, and data 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, standards, security requirements, and technical guidelines • Document Databricks cluster configurations, parameters, and operational standards • Develop and maintain Spark-based solutions using PySpark, Spark SQL, Spark DataFrames, and Datasets • Implement and maintain Delta Lake solutions, including Delta Live Tables where applicable • Optimize data processing, storage, and query performance • Support Palantir Foundry development, including ontologies, ETL/ELT pipelines, applications, and data-driven user interfaces • Integrate Palantir Foundry with enterprise data engineering and analytics environments • Develop and maintain streaming solutions using Kafka, Kafka Streams, ksqlDB, and related technologies • Configure and manage Kafka topics and components, including Schema Registry • Develop and maintain Python-based applications and AWS Lambda functions • Support integration and processing using AWS S3, Kinesis, Lambda, and DynamoDB • Monitor, troubleshoot, and optimize cloud-based data processing solutions • Develop and maintain data quality controls, validation processes, and quality gates • Develop and execute data-driven and unit testing for Spark, Python, and other data processing solutions • Establish and maintain data lifecycle policies covering retention, backup, recovery, and data management • Monitor and troubleshoot pipelines and processing jobs to resolve data quality, performance, and integration issues • Identify improvements to data processing performance, reliability, scalability, and maintainability

🎯 Requirements

• 5+ years of professional data engineering-related experience • Bachelor’s degree in computer science, Engineering, Mathematics, Statistics, or an IT-related field • Must be eligible to obtain and maintain a Secret security clearance • United States Citizenship required for eligibility to obtain a Secret security clearance • Active CompTIA Security+ or CompTIA Network+ certification preferred; if selected, must be able to obtain CompTIA Security+ before beginning program support • Professional experience in data architecture, data engineering, data hubs, data lakes, and/or data warehouses • 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 developing and supporting ETL/ELT pipelines and data transformation processes • Hands-on experience with Databricks required • Experience with Python and SQL • Experience with Apache Spark and/or PySpark 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 in AWS cloud environments, 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, particularly supporting the HC/HR Data Domain, preferred but not required • 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 technology partners, stakeholders, team members, and senior management • Strong written and verbal communication

🏖️ Benefits

• Equal opportunity employer that values diversity at all levels • All individuals, regardless of personal characteristics, are encouraged to apply

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