dataops engineer

SDG Group Middle East

<div>
 
 SDG Group is expanding its global Data &amp; Analytics practice and is seeking a motivated
 
 Data Analytics Engineer
 
 with 3 to 6 years
 
 of experience
 
 in DataOps. The ideal candidate has strong hands-on experience with either
 
 Databricks or Snowflake
 
 , alongside solid understanding of modern cloud data platforms and best practices in data engineering.
 
 
 This role offers a
 
 full-time employment contract in USD
 
 , allowing remote work on
 
 international projects
 
 aligned with the
 
 European working week (Monday to Friday).
 
 
 
 
 
 
 
 
 
 
 
 
 Key Responsibiliti
 
 
 <ul>
 <li>
 esDesign, build, and maintain scalable and reliable data pipelines following DataOps best practic
 </li>
 <li>
 esWork with modern cloud data stacks usin
 
 g Databric
 
 ks (Spark, Delta Lake) o
 
 r Snowfla
 
 ke (Snow pipe, tasks, stream
 </li>
 <li>
 s)Develop and optimize ETL/ELT workflows using Python, SQL, and orchestration too
 </li>
 <li>
 lsWork with Azure data services (ADF, ADLS, Azure SQL, Azure Function
 </li>
 <li>
 s)Implement CI/CD practices using Azure DevOps or Git-based workflo
 </li>
 <li>
 wsEnsure data quality, consistency, and governance across all delivered data solutio
 </li>
 <li>
 nsMonitor and troubleshoot pipelines for performance and operational excellen
 </li>
 <li>
 ceCollaborate with international teams, architects, and analytics consultan
 </li>
 <li>
 tsContribute to technical documentation and solution design asse
 </li>
 </ul>
 
 
 
 
 
 ts
 
 Required Skills &amp; Qualificati
 
 
 <ul>
 <li>
 onsBachelor&rsquo;s degree in computer science, Engineering, Information Systems, or related fi
 </li>
 <li>
 e
 
 ldHands-on experie
 
 nce in DataOps / Data Engineer
 </li>
 <li>
 ingStrong knowledge
 
 in Databricks OR Snowfl
 
 ake (one of them is mandato
 </li>
 <li>
 ry)Proficiency
 
 in Python and
 
 </li>
 <li>
 SQLExperience wi
 
 th Az
 
 ure data ecosystem (ADF, ADLS, Synapse, et
 </li>
 <li>
 c.)Understanding of CI/CD practices and DevOps for da
 </li>
 <li>
 ta.Knowledge of data modeling, orchestration frameworks, and monitoring to
 </li>
 <li>
 olsStrong analytical and troubleshooting ski
 </li>
 <li>
 llsEagerness to learn and grow in a global consulting environm
 </li>
 </ul>
 
 
 entNice to H
 
 
 <ul>
 <li>
 aveExperience with Delta Live Tables, Unity Catalog, or Lakehouse conce
 </li>
 <li>
 ptsKnowledge of BI tools (Power BI, Qli
 </li>
 <li>
 ck)Exposure to Agile / Scrum framewo
 </li>
 <li>
 rksRelevant certifications (Azure Data Engineer, Databricks, Snowfla
 </li>
 </ul>
 
 
 
 
 
 ke)
 
 What We O
 
 
 <ul>
 <li>
 fferRemote working model aligned with international project n
 </li>
 <li>
 eedsFull-time employment contract wit
 
 h a USD-based compensation pac
 
 </li>
 <li>
 kageOpportunity to work on European and global engagem
 </li>
 <li>
 entsMentorship and growth paths within SDG G
 </li>
 <li>
 roupA dynamic, innovative, and collaborative environ
 </li>
 <li>
 mentAccess to world-class training and learning platf
 </li>
 </ul>
 
 
 
 orms
</div>

Senior Data Analytics Engineer

CPI Security

<div>CPI Security, a national leader in residential and commercial security solutions, is seeking a Data Engineer to join us on our data transformational journey. This is an exciting, hands-on opportunity to contribute to the implementation of a modern enterprise data platform at a company that has fully embraced the Snowflake platform. This role will work with line of business leaders and technical users to help design and implement our cloud data warehouse using data vault modeling and dbt. CPI will leverage the data cloud for our data warehouse, machine learning, and AI journeys. The ideal person will have solid experience building and implementing data warehouses in the cloud with experience in data vault modeling and dbt. This is an on-site position at our HQ in Charlotte, NC.

What You'll Do:

Data Vault Implementation Collaborate on the design and implementation of data vault 2.0 modeling patterns to build a scalable, audit-friendly enterprise data platform that supports business agility and data governance.

Modern Data Engineering Build and maintain automated data pipelines using dbt (Cloud/Core), Python, and Snowflake to transform raw data into business-ready datasets with comprehensive data quality testing.

Cloud Data Platform Development Support the implementation of an enterprise data platform on Snowflake, including automated deployment pipelines, data quality frameworks, and monitoring solutions. While we are modernizing to a cloud data platform, on premises work is still needed using SSIS and MSSQL Server.

Data Mart &amp; Dimensional Modeling Contribute to the design and building of data marts using dimensional modeling techniques (Kimball methodology) to support business intelligence and analytics requirements.

ETL/ELT Pipeline Development Design and implement data transformation models using dbt, SQL, and Python to build scalable ingestion and processing pipelines.

Data Quality &amp; Testing Implement data quality testing frameworks using dbt tests, custom Python validations, and automated monitoring to ensure data accuracy and reliability.

External Data Integration Integrate and operationalize data from external systems such as CRM, ERP, and third-party platforms via secure cloud data sharing, CDC, and APIs.

DataOps Implementation Support reliable, scalable, and automated data workflows by implementing DataOps best practices for continuous integration, testing, deployment, and monitoring across the data pipeline lifecycle.

Cloud Migration Support Contribute to planning, designing, and implementing data migration strategies from legacy systems to our modern cloud platform 


What We're Looking For:

Required Experience:
<ul>
<li>4+ years of data engineering experience with cloud data platforms</li>
<li>4+ years of experience with Snowflake (required)</li>
<li>4+ years of experience with dbt (Cloud and/or Core)</li>
<li>4+ years of Python development experience</li>
<li>3+ years of AWS experience</li>
<li>3+ years of experience building data warehouses and data marts</li>
<li>Exposure to or basic understanding of data vault 2.0 modeling methodology</li>
<li>Working knowledge of dimensional modeling (Kimball methodology)</li>
<li>Exposure to automated deployment and CI/CD pipelines</li>
<li>Experience implementing data quality testing frameworks</li>
</ul>
Technical Skills:
<ul>
<li>Strong SQL skills with MSSQL Server and SSIS</li>
<li>Solid understanding of data modeling concepts including dimensional and data vault patterns</li>
<li>Proficient with dbt for data staging, cleaning, transformation, testing, and modeling</li>
<li>Proficiency in Python programming for data engineering tasks</li>
<li>Experience working in agile/scrum teams for data engineering and analytics engineering</li>
<li>Working knowledge of AWS cloud services (S3, Lambda, IAM, CloudFormation, etc.)</li>
<li>Familiarity with data orchestration tools (Airflow, Prefect, or similar)</li>
<li>Understanding of modern data engineering practices and agile methodologies</li>
<li>Awareness of data governance, security, and compliance requirements</li>
</ul>
Preferred Qualifications:
<ul>
<li>AWS Certified Developer certification</li>
<li>Snowflake certifications in data engineering and/or architecture</li>
<li>Experience with data vault automation tools (automate-dv package)</li>
<li>Knowledge of modern BI and analytics platforms (Tableau, Sigma, ThoughtSpot)</li>
</ul>
Soft Skills:
<ul>
<li>Good oral and written communication skills to effectively deliver messages to a range of audiences - from business to technical</li>
<li>Positive team member mindset with eagerness to learn and grow</li>
<li>Strong teamwork and interpersonal skills, with the ability to deliver results working independently or in a collaborative environment</li>
<li>Agile development experience preferred</li>
<li>Solution-oriented approach with good problem-solving abilities</li>
</ul>
Education:
<ul>
<li>Bachelor's degree in Information Systems, Computer Science, Data Science, or related field of study preferred</li>
<li>Work experience equivalent will be considered</li>
</ul>
What Sets You Apart:
<ul>
<li>Good understanding of the data engineering lifecycle</li>
<li>Experience with cloud data platform implementations</li>
<li>Ability to work with cross-functional teams and stakeholders</li>
<li>Passion for building modern, cloud-first data solutions</li>
<li>Strong analytical and critical thinking skills</li>
<li>Commitment to data quality and best practices</li>
</ul>
Why Join CPI Security:
<ul>
<li>Opportunity to contribute to a modern enterprise data platform implementation</li>
<li>Work with cutting-edge cloud technologies and data vault modeling</li>
<li>Collaborative environment with experienced data professionals</li>
<li>Competitive compensation and benefits package</li>
<li>Professional development opportunities and certification support</li>
<li>On-site position in Charlotte, NC with a dynamic, growing company</li>
</ul>
CPI Security is an equal opportunity employer committed to diversity and inclusion in the workplace.</div>

Data Engineer

Qualcomm

<div><h2 class="jobSectionHeader">Company:
</h2>Qualcomm Incorporated
<h2 class="jobSectionHeader">Job Area:
</h2>Information Technology Group, Information Technology Group &gt; IT Data Engineer
General Summary:
We are hiring a Data Platform Engineer to design, build, and operate a modern, data platform with Databricks Lakehouse as a core foundation.
This role is ideal for a senior engineer who excels in system design, platform innovation, and hands‑on execution. You will help design, implement and improve reliability of the data platform, influence architectural direction, and mentor engineers while working closely with data scientists, analysts, and application teams.
This is a hands‑on, high‑impact role with strong ownership across architecture, implementation, reliability, security, and cost optimization.
This role requires full-time onsite work (5 days per week) in either San Diego, CA or Boulder, CO.
Minimum Qualifications:
<ul><li>7+ years of IT-related work experience with a Bachelor's degree in Computer Engineering, Computer Science, Information Systems or a related field.
</li></ul>OR
 
9+ years of IT-related work experience without a Bachelor&rsquo;s degree.
 
 
<ul><li>5+ years of work experience with programming (e.g., Java, Python).
</li><li>3+ years of work experience with SQL or NoSQL Databases.
</li><li>3+ years of work experience with Data Structures and algorithms.
</li></ul>What You&rsquo;ll Do
<ul><li>Design and build scalable, distributed data platform systems
</li><li>Own Databricks workspace architecture, governance, and lifecycle management
</li><li>Implement infrastructure as code using Terraform/Terramate
</li><li>Build and support end‑to‑end data pipelines, from ingestion to analytics and ML
</li><li>Develop and maintain CI/CD pipelines for infrastructure, data pipelines, notebooks, SQL, and ML artifacts
</li><li>Operate and optimize Amazon EKS clusters supporting data workloads
</li><li>Define and monitor SLIs/SLOs for platform reliability and data quality
</li><li>Drive innovation and continuous improvement across platform architecture and tooling
</li><li>Lead incident response, on‑call rotations, and blameless post‑mortems
</li><li>Implement strong security, compliance, and governance controls
</li><li>Mentor engineers and influence platform standards and best practices
</li></ul>Must‑Have Qualifications
System Design &amp; Innovation
<ul><li>Proven experience designing complex, distributed data systems end‑to‑end
</li><li>Strong system design skills across cloud infrastructure, data pipelines, storage, governance, and observability
</li><li>Ability to evaluate and communicate architectural trade‑offs (scalability, reliability, cost, security, operability)
</li><li>Demonstrated innovation mindset, such as:
<ul><li>Modernizing or simplifying legacy data platforms
</li><li>Introducing new architectural patterns or platform capabilities
</li><li>Improving reliability, performance, or developer experience through design
</li></ul></li></ul>Cloud &amp; Data Platform Expertise
<ul><li>8+ years building and operating large‑scale cloud platforms
</li><li>5+ years in Data Platform, DevOps, SRE, or DataOps roles
</li><li>Expert‑level experience with AWS, including networking, IAM, security, and multi‑account environments
</li><li>Strong hands‑on experience with Databricks Lakehouse Platform, including:
<ul><li>Unity Catalog
</li><li>Delta Lake
</li><li>MLflow
</li></ul></li><li>Experience owning Databricks workspace architecture and governance
</li></ul>Infrastructure, Automation &amp; Reliability
<ul><li>Deep experience with Terraform/Terramate (or similar IaC tools)
</li><li>Proven experience building CI/CD pipelines (GitHub Actions, Jenkins)
</li><li>Advanced Python and Bash scripting skills
</li><li>Hands‑on experience managing Amazon EKS clusters and Helm deployments
</li><li>Experience defining and operating SLIs/SLOs for platform reliability and data quality
</li></ul>Security &amp; Leadership
<ul><li>Strong understanding of cloud security best practices
</li><li>Experience supporting SOX, GDPR, or regulated environments
</li><li>AWS Certified DevOps Engineer &ndash; Professional (or equivalent experience)
</li><li>Ability to work independently and mentor team members
</li><li>Strong communication skills to explain complex system designs to technical and non‑technical stakeholders
</li></ul>Nice‑to‑Have
<ul><li>Experience with Acceldata, OpenTelemetry, or data observability tools
</li><li>Experience with Fivetran Hybrid / HVR or enterprise ingestion tools
</li><li>Experience working with Hashicorp vault or similar secret management tools
</li><li>Policy‑as‑code experience using OPA
</li><li>Experience working with static Code analysis tool like Sonar
</li><li>Experience with data lineage or metadata management tools
</li><li>Databricks serverless compute optimization and cost management
</li><li>Experience driving platform strategy across multiple teams distributed globally
</li></ul><div>Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here . Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
</div>To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.
Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. 
Pay range and Other Compensation &amp; Benefits :
$158,400.00 - $237,600.00
The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer &ndash; and you can review more details about our US benefits at this link .
If you would like more information about this role, please contact Qualcomm Careers .</div>

Data Platform Engineer, Senior Staff

Beta Technologies

<div><div>At BETA Technologies, we apply our intellectual curiosity, passion for aviation, and commitment to sustainability toward a shared mission of revolutionizing electric aviation. Regardless of the position one holds, each team member brings their talent and desire to positively impact the environment and lives of others in a refreshing, vibrant, and inclusive culture.</div><div></div><div> 
We are seeking a Platform Engineer to join our Data and AI Platform team, bringing strong hands-on engineering skills and a builder's mindset to help design, deploy, and operate the data and knowledge infrastructure that powers our organization. In this role, you will combine software and data engineering fundamentals with practical experience in cloud-native architectures, graph databases, and API design to build robust, scalable production systems that enable rich data discovery, seamless integration, and reliable access across diverse data sources. You will work collaboratively with data scientists, other platform engineers, and domain experts to evaluate, architect, and implement the most appropriate data solutions, and then roll up your sleeves to build, deploy, and maintain them in production. The ideal candidate is a pragmatic, hands-on technologist who thrives on solving real infrastructure and data challenges end-to-end, from initial design through production operations, and who takes pride in building systems that make data more findable, accessible, and reusable across the enterprise.
</div>
<h3 class="jobSectionHeader">How you will contribute to revolutionizing electric aviation:
</h3><div><ul><li>Design, build, and operate scalable data platform services and frameworks that empower domain teams to manage their data assets within a cohesive enterprise architecture</li>
<li>Implement data integration solutions that create a digital thread connecting information across the entire product lifecycle from design through manufacturing to field operations</li>
<li>Build and maintain data storage systems including data lakes, warehouses, and graph databases that make organizational data accessible and ready to power advanced analytics and AI</li>
<li>Create and extend enterprise data catalog capabilities that document what data exists across organizational systems, how it is structured, and how it connects, enabling teams across the company to navigate the full data landscape</li>
<li>Develop and expose performant data access layers using technologies such as GraphQL and REST APIs, providing intuitive interfaces to complex underlying data</li>
<li>Deploy, monitor, and manage production data systems on cloud infrastructure, ensuring high availability, performance, and reliability</li>
<li>Implement data quality and lineage solutions that ensure accuracy and traceability across diverse data types; essential for aerospace compliance and establishing a trusted foundation for analytics and AI</li>
<li>Build and maintain CI/CD pipelines, infrastructure as code, and automated deployment processes that keep our data platform agile, reproducible, and production-ready</li>
<li>Partner with cross-functional teams on DataOps practices and data governance to keep data assets trusted, accessible, and well-managed.</li>
<li>Actively contribute to a collaborative team environment through code reviews, knowledge sharing, and constructive feedback that continuously improves our data solutions and maintains high engineering standards</li>
</ul></div><h3 class="jobSectionHeader">Minimum Qualifications:
</h3><div><ul><li>Bachelor's degree in Computer Science, Information Systems, Data Science, or related technical field (or equivalent practical experience)</li>
<li>3+ years building and shipping data or platform infrastructure in production, with ownership of system availability, performance, and incident response</li>
<li>Strong software engineering fundamentals including clean code practices, testing, and building maintainable systems</li>
<li>Provisioned, configured, and operated cloud-based data services in production (preferably on AWS)</li>
<li>Built or maintained systems using graph databases (e.g., Neo4j, Amazon Neptune, Stardog) and designed graph data models</li>
<li>Designed and built APIs that other teams or systems depend on, with working knowledge of GraphQL</li>
<li>Proficiency with modern data engineering tools and languages (e.g., Python, SQL)</li>
<li>Designed and built data pipelines and data models that ingest and transform data from diverse sources to serve multiple consumers or use cases</li>
<li>Built and maintained CI/CD pipelines, infrastructure as code, and containerized deployments (e.g. Docker, Kubernetes) for production systems</li>
<li>Strong troubleshooting skills with the ability to diagnose and resolve issues across the full stack from infrastructure through application layers</li>
<li>Excellent communication skills with the ability to translate technical concepts for diverse audiences</li>
</ul></div><h3 class="jobSectionHeader">Above and Beyond Qualifications:
</h3><div><ul><li>5+ years of experience building and operating production data platforms at scale</li>
<li>Experience with semantic technologies including knowledge graphs, ontology design, and related standards (e.g., RDF, OWL, SPARQL, SHACL, RML/R2RML)</li>
<li>Familiarity with AI-assisted development tools such as agentic coding assistants, gained through practical use</li>
<li>Experience with distributed computing frameworks (e.g., Spark) and/or event-driven and streaming architectures (e.g., Kafka, Kinesis)</li>
<li>Hands-on experience with metadata management platforms and enterprise data catalogs</li>
<li>Implemented data lineage and data quality solutions at scale</li>
<li>Experience with monitoring, observability, and alerting for production data systems</li>
<li>Experience working in regulated industries or with complex data governance frameworks</li>
<li>Familiarity with aerospace or manufacturing data standards and regulations</li>
<li>Knowledge of IoT protocols and time-series data management</li>
</ul></div><div>Build electric airplanes with us!</div><div></div><div> 
BETA offers a competitive Total Compensation package designed to support you now and as you grow with us. This role includes both Restricted Stock Units and Performance Stock Units for all full-time team members, so everyone shares in our success. You&rsquo;ll have access to onsite healthcare in Vermont, comprehensive medical coverage, dental and vision, short- and long-term disability, and paid parental leave. We also take care of the everyday details with daily lunch provided, and yes&mdash;flight lessons are part of the experience, along with a range of additional perks that make work here genuinely rewarding.</div><div></div><div> 
We encourage all driven candidates to apply, even if they do not meet every listed qualification.</div><div></div><div> 
We are an equal opportunity employer. Employment decisions are based on merit, competence and qualifications and will not be influenced in any manner on race, color, religion, age, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, disability, veteran or military status, genetic information, pregnancy, or any other protected characteristic under federal, state, or local law. BETA complies with all applicable federal, state and local non-discrimination laws and does not tolerate discrimination of any kind in our workplace.</div><div></div><div> 
Employment offers are contingent upon the successful completion of a background check. BETA Technologies participates in E-Verify.</div>

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.</div>

Data Platform Engineer | Digital Operations

JobNimbus

<div><div><div>Lehi, UT
</div><div>Full Time
</div><div>Mid Level</div></div><div> 
</div><div>We are obsessed with the hero's journey at JobNimbus. Every person has a hero's journey. Hermione Granger, James T. Kirk, Frodo Baggins, Anna &amp; Elsa, Nacho Libre, and even YOU! This is our &ldquo;call to adventure&rdquo; to come check out JobNimbus. What do you have to lose? You might make a few new friends, learn about a sick new company doing some amazing things, and maybe you&rsquo;ll even land a new job!<h2 class="jobSectionHeader">
Mission:</h2>
Own data components with confidence and reliability. Build pipelines or infrastructure that others can depend on with observability, documentation, and quality built in from day one. Expand your impact beyond individual tickets and raise the effectiveness of the entire team.<h2 class="jobSectionHeader">
What you&rsquo;ll be doing:</h2><ul><li>
Design, build, and deploy data pipelines or infrastructure components independently</li><li>
Own 1 to 2 components end to end with monitoring, alerting, and runbooks in place</li><li>
Implement SLIs for data freshness and quality or infrastructure availability</li><li>
Participate in the primary on call rotation and triage incidents for systems you own</li><li>
Write and maintain runbooks for new and existing systems</li><li>
Review pull requests regularly and provide actionable, thoughtful feedback</li><li>
Automate at least one repetitive task per quarter and measure time saved</li><li>
Use AI tools effectively for code generation while validating accuracy, security, and performance before merge</li><li>
Collaborate with analytics, product, and engineering teams to understand downstream dependencies</li><li>
Document systems clearly so others can operate and extend them confidently</li></ul>
<h2 class="jobSectionHeader">
What makes you the hero for this job:</h2><ul><li>
Solid proficiency in SQL and Python for Data Engineering or Terraform and Python for DataOps</li><li>
Ability to design and deploy components without step by step guidance</li><li>
Strong observability mindset with monitoring and alerting built in from day one</li><li>
Comfort participating in on call and handling incident response appropriately</li><li>
Experience writing documentation and runbooks that others can actually follow</li><li>
Habit of automating repetitive work and measuring impact</li><li>
Ability to give meaningful code review feedback that improves system reliability</li><li>
Clear communicator who understands who depends on the systems you build</li><li>
Disciplined in validating AI generated code and catching subtle errors before merge</li></ul> 
 Values:<ul><li>
Extreme Ownership. Impact. Urgent. Accountability. Decisiveness. Happy never satisfied.</li><li>
Customer Obsessed. Everything we build should leave our customers saying, &quot;Aw dip. This product is off the charts cool. Whoever wrote that code deserves a raise!&quot;</li><li>
Proactive Learning. You stay ahead of the curve, continuously learning and implementing cutting-edge technologies.</li><li>
Team Commitment. You build, mentor, and lead a high-performance engineering team that delivers results together.</li><li>
Self Awareness. You know your strengths, weaknesses, and how to surround yourself with the right talent to succeed.</li></ul> 
Mentor (Hit us up to get more information)
Nick Cook - Specialist in hiring amazing people, lover of all things outdoors, computer nerd, and lead substitute on his friends hockey team. 
JobNimbus is proud to be an equal opportunity / affirmative action employer. We are committed to equal opportunity regardless of race, color, religion, sex, national origin, sexual orientation, gender identity, age, disability, Veteran status, or other legally protected characteristics. This position may require the successful completion of a criminal background check and/or drug screen. If you have a disability or special need that requires accommodation, please let us know in the application.
If you have any questions regarding this job post, please email jobs@jobnimbus.com.</div></div>

WinWire

<div>Experience: 15&ndash;18 years
Job Description:
<ul>Presales Excellence: Expertise in solution shaping, differentiated proposals, estimations, storytelling, and deal strategy.
Modern Data &amp; AI Expertise: Deep experience across Data Modernization, Data Engineering, BI Modernization, Data Products, Data Governance, and AI-ready data architectures.
Platform Mastery: Strong hands-on understanding of Microsoft Fabric, Microsoft Purview, Microsoft Power BI, Databricks Lakehouse, SQL Server, and cloud-native data architectures.
AI &amp; ML Orientation: Knowledge of Data Science, Machine Learning workflows, and Agentic AI approaches for BI modernization and intelligent data pipelines.
Healthcare Experience (Preferred): Exposure to healthcare data models, compliance frameworks (HIPAA/PHI), and domain-specific analytics.
Outstanding Communication: Ability to simplify complex topics, influence senior stakeholders, and present compelling narratives.
Business-Centric Mindset: Strong proficiency in value articulation, business case creation, and ROI/TCO modeling.
</ul>
The Data &amp; AI Presales Lead will drive end-to-end presales engagements for Data, Analytics, and AI transformation initiatives. This role blends solution consulting, architectural leadership, and business value narration to shape winning solutions on platforms like Microsoft Fabric, Databricks, Microsoft Purview, and Power BI. The Data &amp; AI Presales Lead will drive end-to-end presales engagements for Data, Analytics, and AI transformation initiatives. This role blends solution consulting, architectural leadership, and business value narration to shape winning solutions on platforms like Microsoft Fabric, Databricks, Microsoft Purview, and Power BI.
Key Responsibilities:
Presales Leadership &amp; Solution Consulting
<ul>Lead presales engagements across global markets for mid-to-large opportunities.
Own RFP/RFI responses, solution narratives, estimation models, and differentiated value propositions.
Partner with Sales, Delivery, and Practice teams to define deal strategy and competitive positioning.
Create persuasive presentations, demos, workshops, and customer-facing collateral.
Build business cases including ROI, TCO, and modernization impact assessments.
</ul>
Data Platform &amp; Architecture Design
<ul>Architect high-level designs for:
Data Migration &amp; Modernization (legacy Microsoft Fabric / Databricks / cloud-native platforms)
Lakehouse and Data Mesh architecture
AI Ready Data
BI Modernization using Microsoft Power BI and Microsoft Fabric
Data Products and domain-driven architectures
Define ingestion-to-consumption pipelines: storage, transformation, governance, observability.
Provide estimation, sizing, and architectural guardrails for scalable, secure, and cost-optimized solutions.
</ul>
Data Governance, Quality &amp; Observability
<ul>Design frameworks for Data Governance, Data Stewardship, Data Quality, and Data Observability.
Use Microsoft Purview for data cataloging, lineage, classification, and compliance needs.
Define security models aligned with enterprise and regulatory requirements.
</ul>
AI-Ready Data, ML Workflows. DataOPS &amp; Agentic AI
<ul>Craft AI-ready data strategies to support advanced analytics, ML, and GenAI workloads.
Define solution patterns for:
Agentic AI for Data Engineering, Data Science
ML model lifecycle and operationalization
Agentic AI for BI modernization (semantic automation, intelligent insights, smart metadata utilization)
DataOPS
Partner with Data Science teams to ensure platform readiness for AI workloads.
</ul>
Healthcare Vertical (Added Advantage)
<ul>Understand healthcare datasets (EHR/EMR, claims, clinical data) and compliance models (HIPAA/PHI).
Contribute to solutions for provider, payer, and clinical analytics use cases.
Advise on secure and compliant healthcare-centric data architectures.
</ul>
Required Skills &amp; Experience
<ul>15&ndash;18 years in Data, Analytics, AI, and modern data platforms.
Strong presales experience with end-to-end ownership of solutions, proposals, and deal strategy.
<div>Hands-on expertise with:
<ul>Microsoft Fabric
Microsoft Power BI
Microsoft Purview
Databricks Lakehouse
SQL Server
Data Governance, Data Quality, Data Observability
</ul></div>Knowledge of Data Engineering, Machine Learning, and Data Science workflows.
Exceptional communication, executive presentation skills, and solution storytelling.
</ul>
Preferred Certifications
<ul>Microsoft Azure Data Engineer / Solutions Architect
Power BI or Microsoft Fabric certifications
Databricks Data Engineer / Lakehouse certifications
GCP Professional Data Engineer (optional)
</ul>
Key Skills: Data &amp; AI, Presales, RFP/RFI, Data governance, BI Modernization</div>

Data & AI Presales Lead

Golden Technology

<div>
 The team is seeking a Data Engineer experienced in implementing modern data solutions in Azure, with strong hands-on skills in Databricks, Spark, Python, and cloud-based DataOps practices. The Data Engineer will analyze, design, and develop data products, pipelines, and information architecture deliverables, focusing on data as an enterprise asset. This role also supports cloud infrastructure automation and CI/CD using Terraform, GitHub, and GitHub Actions to deliver scalable, reliable, and secure data solutions.
 
 
 
 Requirements
 
 
 
 <ul>
 <li>
 5+ years of experience as a Data Engineer
 </li>
 <li>
 Hands-on experience with Azure Databricks, Spark, and Python
 </li>
 <li>
 Experience with Delta Live Tables (DLT) or Databricks SQL
 </li>
 <li>
 Strong SQL and database background
 </li>
 <li>
 Experience with Azure Functions, messaging services, or orchestration tools
 </li>
 <li>
 Familiarity with data governance, lineage, or cataloging tools (e.g., Purview, Unity Catalog)
 </li>
 <li>
 Experience monitoring and optimizing Databricks clusters or workflows
 </li>
 <li>
 Experience working with Azure cloud data services and understanding how they integrate with Databricks and enterprise data platforms
 </li>
 <li>
 Experience with Terraform for cloud infrastructure provisioning
 </li>
 <li>
 Experience with GitHub and GitHub Actions for version control and CI/CD automation
 </li>
 <li>
 Strong understanding of distributed computing concepts (partitions, joins, shuffles, cluster behavior)
 </li>
 <li>
 Familiarity with SDLC and modern engineering practices
 </li>
 <li>
 Ability to balance multiple priorities, work independently, and stay organized
 
 
 </li>
 </ul>
 Key Responsibilities
 
 
 <ul>
 <li>
 Analyze, design, and develop enterprise data solutions with a focus on Azure, Databricks, Spark, Python, and SQL
 </li>
 <li>
 Develop, optimize, and maintain Spark/PySpark data pipelines, including managing performance issues such as data skew, partitioning, caching, and shuffle optimization
 </li>
 <li>
 Build and support Delta Lake tables and data models for analytical and operational use cases
 </li>
 <li>
 Apply reusable design patterns, data standards, and architecture guidelines across the enterprise, including collaboration with when needed
 </li>
 <li>
 Use Terraform to provision and manage cloud and Databricks resources, supporting Infrastructure as Code (IaC) practices
 </li>
 <li>
 Implement and maintain CI/CD workflows using GitHub and GitHub Actions for source control, testing, and pipeline deployment
 </li>
 <li>
 Manage Git-based workflows for Databricks notebooks, jobs, and data engineering artifacts
 </li>
 <li>
 Troubleshoot failures and improve reliability across Databricks jobs, clusters, and data pipelines
 </li>
 <li>
 Apply cloud computing skills to deploy fixes, upgrades, and enhancements in Azure environments
 </li>
 <li>
 Work closely with engineering teams to enhance tools, systems, development processes, and data security
 </li>
 <li>
 Participate in the development and communication of data strategy, standards, and roadmaps
 </li>
 <li>
 Draft architectural diagrams, interface specifications, and other design documents
 </li>
 <li>
 Promote the reuse of data assets and contribute to enterprise data catalog practices
 </li>
 <li>
 Deliver timely and effective support and communication to stakeholders and end users
 </li>
 <li>
 Mentor team members on data engineering principles, best practices, and emerging technologies
 </li>
 </ul>
</div>

Data Engineer 2

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