senior data engineer

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data platform engineer

NiCE Actimize

<div><div><p>At NiCE, we don&rsquo;t limit our challenges. We challenge our limits. Always. We&rsquo;re ambitious. We&rsquo;re game changers. And we play to win. We set the highest standards and execute beyond them. And if you&rsquo;re like us, we can offer you the ultimate career opportunity that will light a fire within you.</p></div><div><p><b>
Overview</b></p>
<p><b>
We are hiring a Senior Data Engineer to support our engineering data initiatives while collaborating with teams across SLC and Pune. The Senior Engineer will work closely with the Lead Engineer and key partners across the organization to execute critical components of our data strategy.</b></p>
<p><b>
Key Responsibilities</b></p>
<ul>
<li>Develop, optimize, and maintain data pipelines and data platform components.</li>
</ul><ul><li>Implement solutions supporting data federation, semantic modeling, and data governance frameworks.</li>
</ul><ul><li>Collaborate with Engineering, Analytics, and Product teams to deliver highquality data assets.</li>
</ul><ul><li>Apply AIdriven tools to accelerate development and improve data quality and productivity.</li>
</ul><ul><li>Investigate and adopt emerging data technologies aligned with organizational strategy.</li>
</ul><ul><li>Operate independently and deliver consistent results within distributed team environments.</li>
</ul>
<p><b>Required Technical Background</b></p><br>
<p></p>
<ul>
<li>Strong expertise with Snowflake (highest priority).</li>
</ul><ul><li>Hands-on experience with Kafka, Flink, Spark, and Airflow.</li>
</ul><ul><li>Experience with semantic layers (e.g., Cube).</li>
</ul><ul><li>Experience with federated data layers (e.g., Trino).</li>
</ul><ul><li>Knowledge of distributed systems and modern data engineering patterns.</li>
</ul><ul><li>Proficiency with AI tools supporting data engineering workflows.</li></ul><br>
<p></p>
<p><b>
Preferred Qualifications</b></p>
<ul>
<li>Experience supporting or contributing to largescale data initiatives.</li>
</ul><ul><li>Strong selfdirection, problemsolving abilities, and eagerness to learn new technologies.</li>
</ul><ul><li>Solid communication and collaboration skills across remote teams.</li></ul></div><p></p><div><p><b><i><br>
About NiCE
</i></b></p><p><i>NICE Ltd. (NASDAQ: NICE) software products are used by 25,000+ global businesses, including 85 of the Fortune 100 corporations, to deliver extraordinary customer experiences, fight financial crime and ensure public safety. Every day, NiCE software manages more than 120 million customer interactions and monitors 3+ billion financial transactions.
</i></p><p><i>Known as an innovation powerhouse that excels in AI, cloud and digital, NiCE is consistently recognized as the market leader in its domains, with over 8,500 employees across 30+ countries.
</i></p><p><i>NiCE is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, age, sex, marital status, ancestry, neurotype, physical or mental disability, veteran status, gender identity, sexual orientation or any other category protected by law.</i></p></div></div><p></p>

Senior Software Engineer,CX – Platform Data

Metas Solutions

<div><p><b>Metas Solutions</b> has an <b>&quot;</b><b><i>opening&quot;</i></b> for a talented <b>Senior Data Engineer </b>based in <b>Atlanta</b>,<b> GA</b>. The ideal candidate must be able to work onsite in the Atlanta metro area and someone who's proficient in Databricks workspaces and Azure infrastructure. In this position, you'll drive the next generation of our analytics products by architecting and delivering end-to-end cloud analytics solutions. In a fully cloud-native environment, you'll partner with product managers, data scientists, software engineers, machine learning (ML) engineers and business analysts to enable and support a platform that powers personalized experiences and operational efficiency. You'll leverage automated model CI/CD, containerized deployments (Docker/Kubernetes), and real-time monitoring to ensure our ML systems are reliable, secure, and scalable.</p><p>
You will be responsible for the design, implementation, and maintenance of the Databricks workspaces and its associated Azure infrastructure. You will manage and optimize data and machine learning workloads, ensuring a reliable, secure, and scalable platform for business analysts, data engineering and data science teams.</p><p><b>
Responsibilities:</b></p><ul><li>
Lead the administration and governance framework of the platform regarding the security posture of the enterprise and its key stakeholders</li><li>
Design and implement automated solutions to streamline accounts and workspace administration</li><li>
Collaborate with cross-functional teams to understand business needs and translate them into ML solutions</li><li>
Mentor junior engineers and provide technical leadership in Databricks best practices and techniques</li><li>
Conduct cost and performance analysis of the various computes, and data assets within the platform</li><li>
Stay current with the latest advancements in Databricks SQL, Machine Learning and AI, and integrate new technologies and methods as applicable</li><li>
Engage in knowledge sharing and contribute to building a strong, collaborative team environment</li></ul><p><b>
Qualifications:</b></p><ul><li>
5+ years of experience with Databricks Account and Workspace Administration, including governance, configuration, and security management</li><li>
Experience with optimizing Databricks environments for cost efficiency, performance, and reliability</li><li>
Experience with developing and maintaining Databricks data pipelines using Autoloader, Delta Live Tables, and Databricks Workflows</li><li>
Experience with implementing MLOps solutions using MLflow 2.0/3.0, Serving Endpoints, and Model Registry in production environments</li><li>
Experience with Databricks SQL tools such as Queries and AI/BI Dashboards</li><li>
Experience with large datasets and distributed computing across cloud platforms (AWS, GCP, Azure), including Azure services like Entra ID, Data Factory, Key Vault, and Purview</li><li>
Knowledge of Unity Catalog Governance Architecture and enterprise data security best practices</li><li>
Possession of strong communication and documentation skills with the ability to clearly convey complex technical concepts to both technical and non-technical audiences</li><li>
Ability to work on-site in Atlanta, Georgia</li><li>
Master's degree in computer science, Computer Engineering, or related programs</li></ul><p><b>
Additional Qualifications:</b></p><ul><li>
Knowledge of Azure Cloud Networking concepts like VNET Injection</li><li>
Databricks Platform Administrator Certification</li><li>
Microsoft Certified: Azure Administrator Associate</li></ul><p><b>
Security Requirements:</b></p><ul><li>
Must be US Citizen and with the ability to obtain a US Government security clearance (Public Trust 5) within a reasonable period</li><li>
Market competitive salary, commensurate with experience and education</li><li>
Comprehensive benefits package available, Medical, Dental, Vision and Life Insurance, Paid Time Off (PTO), 401K with company match, growth, and promotion opportunities</li></ul><p>
</p><p><b><i>We are an Equal Opportunity Employer/Veterans/Disabled</i></b></p></div>

Senior Data Engineer

Capgemini

<div><div><div><p>Atlanta</p><div>
Senior GCP Data Engineer</div><p>
</p></div></div><p></p><div><div><div><div><div><p>
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you&rsquo;d like, where you&rsquo;ll be supported and inspired by a collaborative community of colleagues around the world, and where you&rsquo;ll be able to reimagine what&rsquo;s possible. Join us and help the world&rsquo;s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.</p><div><div><div><div>
Job Description</div></div><div>
Data engineers are responsible for building reliable and scalable data infrastructure that enables organizations to derive meaningful insights, make data-driven decisions, and unlock the value of their data assets.</div></div><div><div><div>
Location</div></div><div><p>
This job is based in Atlanta, GA and Nashville, TN requiring hybrid work participation.</p></div></div><div><div><div>
About the job you're considering</div></div><div><p>
Looking for a GCP Data Engineer with strong Data Engineering experience to build and maintain complex technology initiatives. Your role will involve hands-on development and implementation of data platforms on Google Cloud Platform.
</p></div></div><div><div><div>Your role</div></div><div><p>
Build, develop, and maintain end-to-end data pipelines (ETL/ELT) on Google Cloud Platform.<br>
Implement data ingestion, processing, storage, and analytics using BigQuery, Dataflow, Pub/Sub, Cloud Storage, Dataproc, and Composer.<br>
Implement modern data lakehouse and data warehouse architectures aligned with analytics and AI use cases.<br>
Ensure data quality, validation, and adherence to data governance and security standards.<br>
Develop infrastructure as code using Terraform or equivalent tools.<br>
Collaborate with architects and platform teams on CI/CD, DataOps, and monitoring strategies.<br>
Apply GCP security best practices, including IAM, networking, encryption, and compliance controls.<br>
Partner with business and technology stakeholders to translate technical designs into functional, efficient code.<br>
Act as a technical developer on cloud data modernization and GCP best practices.<br>
Support solution implementation, including testing, debugging, and production support.
</p></div></div><div><div><div>Your skills and experience</div></div><div><p>
Required: 5+ years of overall IT experience with 3+ years specifically in cloud data engineering.<br>
Required: Proven experience building and deploying GCP-based data pipelines.<br>
Background with large enterprise data programs across industries.<br>
Deep expertise in Google Cloud Platform, including BigQuery, Cloud Storage, Dataflow (Apache Beam), Pub/Sub, Dataproc (Spark), and Composer (Airflow).<br>
Strong knowledge of data modeling, ETL/ELT, streaming architectures, and SQL.<br>
Experience with CI/CD, Terraform, and DataOps practices.<br>
Exposure to AI/ML enablement on GCP (Vertex AI is a plus).<br>
Required: Google Professional Data Engineer Certification.<br>
Strong communication and stakeholder management abilities.<br>
Ability to explain technical concepts to technical and non-technical audiences.<br>
Experience working in global, distributed teams.<br>
Passion for innovation, engineering excellence</p></div></div></div><p>
The base compensation range for this role in the posted location is $76,200 to $ 187,740</p><p>
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.</p><p>
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.</p><p>
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.</p><p>
It is not typical for candidates to be hired at or near the top of the posted compensation range.</p><p>
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.</p><p>
</p><p>Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
</p><ul><li>Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave</li></ul><ul><li>
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)</li><li>
Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)</li><li>
Life and disability insurance</li><li>
Employee assistance programs</li><li>
Other benefits as provided by local policy and eligibility</li></ul><p>
Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini&rsquo;s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.</p><p>
</p><p>Disclaimers</p><p>
Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.</p><p>
This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.</p><p>
Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.</p><p></p><p><br>
</p><p>Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.</p><p>
</p></div></div><div><div><div><div><div>Ref. code</div><div>
428467-en_US</div></div><div><div>
Posted on</div><div>
27 Feb 2026</div></div><div><div>
Experience level</div><div>
Experienced Professionals</div></div><div><div>
Contract type</div><div>
Permanent</div></div><div><div>
Location</div><div>
Atlanta</div></div><div><div>
Business unit</div><div>
I and D Global Business Line</div></div><div><div>
Brand</div><div>
Capgemini</div></div><div><div>
Professional communities</div><div>
Data &amp; AI</div></div></div></div></div></div></div></div></div><p></p>

Senior GCP Data Engineer

Equifax

<div><p>Equifax is seeking a driven Data Engineer to contribute to the creation of high-quality datasets that power our analytical capabilities. If you are a data enthusiast with a knack for databases and a talent for extracting meaningful insights from complex data, we encourage you to apply.
</p><p>You will partner with internal stakeholders to design and deliver analytical solutions in an automated and mature fashion.
</p><p>Strong communication skills are required, and financial industry experience is preferred. This position provides an opportunity to work with best-in-class technology and a rich big data ecosystem.
</p><p><b>This position is based out of our Atlanta, Georgia (OAC) office. We are required to be in the office 3 days/week - Tues/Wed/Thurs.
</b></p><p><b>This position does not offer immigration sponsorship (current or future) including F-1 STEM OPT extension support.
</b></p><p><b>This position is </b><b>not </b><b>open to third-party vendors or C2C.<br>
</b><br>
</p><p><b>What you will do
</b></p><ul><li><p>Integrate, consolidate, cleanse and structure data for use by our analysts.
</p></li><li><p>Analyze, understand and prepare complex and new data sources and incorporate them into project design.
</p></li><li><p>Use analytical insights to develop solutions, improve processes and work with counterparts in the business to implement proposed solutions.
</p></li><li><p>Create SQL and Python Pipelines that are optimized, efficient, repeatable and scalable.
</p></li><li><p>Perform design, creation, and interpretation of large and highly complex datasets.
</p></li><li><p>Utilize AI to accelerate development, optimize code, and create processing documentation for data pipelines.
</p></li><li><p>Understand best practices for data management, maintenance, and reporting and use that knowledge to implement improvements in our solutions.
</p></li><li><p>Develop and implement data quality checks and troubleshoot data anomalies.
</p></li><li><p>Stay up-to-date with the latest trends and advancements in GCP and related technologies, actively proposing and evaluating new solutions.
</p></li></ul><p><b>What experience you will need
</b></p><ul><li><p>BS degree in a STEM major or equivalent discipline.
</p></li><li><p>5-7 years of experience in data related profession, with a minimum of 2 years as a data engineer.
</p></li><li><p>Extensive experience in SQL is a must, as well as strong knowledge of Python.
</p></li><li><p>Experience building and maintaining moderately-complex data pipelines, troubleshooting issues, transforming and entering data into a data pipeline in order for the content to be digested and usable for future projects.
</p></li></ul><p><b>What could set you apart
</b></p><ul><li><p>A master's degree in a related field is a strong plus.
</p></li><li><p>Experience developing code using AI tools such as Gemini, Chat GPT, Claude, Co - Pilot, etc.
</p></li><li><p>Background in credit risk or finance.
</p></li><li><p>Experience working with large datasets on a big data platform (e.g., Google Cloud, AWS, Snowflake, Hadoop).
</p></li><li><p>Intermediate level understanding and experience with Google Cloud Platforms and overall cloud computing concepts (ie AirFlow), as well as basic knowledge of other cloud environments.
</p></li><li><p>Advanced Git or equivalent usage and CI/CD integration skills.
</p></li></ul><p>#LI-Hybrid
</p><p>#LI-KD1</p></div>

Data Engineer

The Home Depot

<div><p><b>Position Purpose:</b></p><p>
The Sr Machine Learning Engineer is responsible for joining a product team and contributing to the software design, algorithm design, and overall product lifecycle for a product that our users love. The engineering process is highly collaborative. Sr ML Engineers are expected to pair daily as they work through user stories and support products as they evolve.</p><p><br>
ML Engineers may be involved in designing and implementing AI/ML algorithms to embed directly into software products. Activities may include using specific HD process techniques, integration, design, and development. The role could interface with Business Stakeholders, Technology Infrastructure teams, and Development teams to ensure that business requirements are properly met within a machine learning solution. The role may also be involved in performance tuning, testing, and product monitoring. Other responsibilities may include performing customer outreach, designing ML educational material, and data engineering.</p><p><br>
Sr ML Engineers should be able to operate independently though will typically work as part of a team with varying skill levels to create, support, and deploy production applications. This role will review submitted code and provide feedback to improve, based on best practices.</p><p><b><br>
Key Responsibilities:</b></p><ul><li>
70% Delivery and Execution - Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions; Documents, reviews, and ensures that all quality and change control standards are met; Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable; Writes custom code or scripts to automate infrastructure, monitoring services, and test cases; Writes custom code or scripts to do &quot;destructive testing&quot; to ensure adequate resiliency in production; Configures commercial off the shelf solutions to align with evolving business needs; Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively</li><li>
10% Learning - Participates in learning activities around modern software design, machine learning, and development core practices (communities of practice); Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations</li><li>
20% Support and Enablement - Fields questions from other product teams or support teams; Monitors tools and participates in conversations to encourage collaboration across product teams; Provides application support for software running in production; Proactively monitors production Service Level Objectives for products; Proactively reviews the Performance and Capacity of all aspects of production: code, infrastructure, data, message processing, and prediction quality</li></ul><p><b><br>
Direct Manager/Direct Reports:</b></p><ul><li>
This Position typically reports to Software Engineer Manager or Sr. Software Engineer Manager</li><li>
This Position has 0 Direct Reports</li></ul><p><b><br>
Travel Requirements:</b></p><ul><li>
Typically requires overnight travel 5% to 20% of the time.</li></ul><p><b><br>
Physical Requirements:</b></p><ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul><p><b><br>
Working Conditions:</b></p><ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul><p><b><br>
Minimum Qualifications:</b></p><ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul><p><b><br>
Preferred Qualifications:</b></p><ul><li>
2 - 4 years of relevant work experience</li><li>
Experience to algorithms such as clustering, forecasting, anomaly detection, and neural networks.</li><li>
Experience to basic statistics and regression algorithms</li><li>
Experience with Data Analysis and Machine Learning Tools and Libraries like Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, tensorflow, pytorch, etc</li><li>
Experience in Google Cloud Platform and AI/ML related components such as Vertex AI, BigQueryML, and Experience in effective data engineering practices and big data platforms such as BigQuery, Data Store, etc- Experience in a modern scripting language (preferably Python)</li><li>
Experience with GPU acceleration (i.e. CUDA and cuDNN)</li><li>
Experience in modern web application framework such as Node.js</li><li>
Experience in a front-end technology and framework such as HTML, CCS, JavaScript, ReactJS, D3</li><li>
Experience in writing SQL queries against a relational database</li><li>
Experience in version control systems (preferable Git)</li><li>
Experience in a Linux or Unix based environment</li><li>
Experience in a CI/CD toolchain</li><li>
Experience in REST and effective web service design</li><li>
Familiarity with production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security</li><li>
Familiarity with NoSQL databases</li><li>
Familiarity with cloud computing platform and associated automation patterns and machine learning services they provide</li><li>
Familiarity with defensive coding practices and patterns for high Availability</li><li>
Familiarity with A/B testing and effective REST design for scalable web services architecture</li><li>
Familiarity with advanced machine learning techniques such as NLP, convolutional neural networks, autoencoders, and embeddings generation and utilization</li></ul><p><b><br>
Minimum Education:</b></p><ul><li>
The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.</li></ul><p><b><br>
Preferred Education:</b></p><ul><li>
No additional education</li></ul><p><b><br>
Minimum Years of Work Experience:</b></p><ul><li>
2</li></ul><p><b><br>
Preferred Years of Work Experience:</b></p><ul><li>
No additional years of experience</li></ul><p><b><br>
Minimum Leadership Experience:</b></p><ul><li>
None</li></ul><p><b><br>
Preferred Leadership Experience:</b></p><ul><li>
None</li></ul><p><b><br>
Certifications:</b></p><ul><li>
None</li></ul><p><b><br>
Competencies:</b></p><ul><li>
Global Perspective</li><li>
Manages Ambiguity</li><li>
Nimble Learning</li><li>
Self-Development</li><li>
Collaborates</li><li>
Cultivates Innovation</li><li>
Situational Adaptability</li><li>
Communicates Effectively</li><li>
Drives Results</li><li>
Interpersonal Savvy</li></ul></div><p></p>

Senior Machine Learning Engineer (Remote)

<div><p><b>Position Purpose:</b></p><p>
The Staff Machine Learning Engineer is responsible for joining a product team and contributing to the software design, algorithm design, and overall product lifecycle for a product that our users love. The engineering process is highly collaborative. Staff ML Engineers are expected to pair daily as they work through user stories and support products as they evolve.</p><p><br>
ML Engineers may be involved in designing and implementing AI/ML algorithms to embed directly into software products. Activities may include using specific HD process techniques, integration, design, and development. The role could interface with Business Stakeholders, Technology Infrastructure teams, and Development teams to ensure that business requirements are properly met within a machine learning solution. The role may also be involved in performance tuning, testing, and product monitoring. Other responsibilities may include performing customer outreach, designing ML educational material, and data engineering.</p><p><br>
Staff ML Engineers will be a core player on the product team and are expected to build and grow skillsets of more junior engineers. You will also be able to drive multiple ML initiatives by directing algorithm and technology product design</p><p><b><br>
Key Responsibilities:</b></p><ul><li>
45% Delivery and Execution - Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions, Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable; Configures commercial off the shelf solutions to align with evolving business needs; Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively</li><li>
15% Learning - Participates in learning activities around modern software design, machine learning, and development core practices (communities of practice); Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations; Attends conferences and learns how to apply new innovations and technologies where appropriate</li><li>
20% Strategy and Planning - Researches and analyzes business trends and behavioral data to identify opportunities for improvement and new initiatives; Leads the evaluation development and recommendation of specific technology products and platforms to provide cost-effective solutions that meet business and technology requirements; Researches and designs best fit infrastructure, network, database, security, and machine learning architectures for products; Proactively creates and maintains tools for monitoring and support; Participates in project planning and management across multiple efforts; Develops formal training courses</li><li>
20% Support and Enablement - Fields questions from other product teams or support teams; Monitors tools and participates in conversations to encourage collaboration across product teams; Provides application support for software running in production; Proactively monitors production Service Level Objectives for products; Proactively reviews the Performance and Capacity of all aspects of production: code, infrastructure, data, message processing, and prediction quality</li></ul><p><b><br>
Direct Manager/Direct Reports:</b></p><ul><li>
This Position typically reports to Software Engineer Manager or Sr Software Engineer Manager</li><li>
This Position has 0 Direct Reports</li></ul><p><b><br>
Travel Requirements:</b></p><ul><li>
Typically requires overnight travel 5% to 20% of the time.</li></ul><p><b><br>
Physical Requirements:</b></p><ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul><p><b><br>
Working Conditions:</b></p><ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul><p><b><br>
Minimum Qualifications:</b></p><ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul><p><b><br>
Preferred Qualifications:</b></p><ul><li>
3 - 6 years of relevant work experience</li><li>
Experience to algorithms such as clustering, forecasting, anomaly detection, and neural networks.</li><li>
Experience to basic statistics and regression algorithms</li><li>
Experience in advanced machine learning techniques such as NLP, convolutional neural networks, autoencoders, and embeddings generation and utilization</li><li>
Experience in training machine learning models with extremely large datasets</li><li>
Experience with Data Analysis and Machine Learning Tools and Libraries like Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, tensorflow, pytorch, etc.</li><li>
Experience with GPU acceleration (i.e. CUDA and cuDNN)</li><li>
Experience in Google Cloud Platform and AI/ML related components such as Vertex AI, BigQueryML, and AutoML</li><li>
Experience in effective data engineering practices and big data platforms such as BigQuery, Data Store, etc</li><li>
Experience in a modern scripting language (preferably Python)</li><li>
Experience in modern web application framework such as Node.js</li><li>
Experience in a front-end technology and framework such as HTML, CCS, JavaScript, ReactJS, D3</li><li>
Experience in writing SQL queries against a relational database</li><li>
Experience in version control systems (preferable Git)</li><li>
Experience in a Linux or Unix based environment</li><li>
Experience in a CI/CD toolchain</li><li>
Experience in REST and effective web service design</li><li>
Experience in production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security</li><li>
Experience in NoSQL databases</li><li>
Experience in cloud computing platform and associated automation patterns and machine learning services they provide</li><li>
Experience in defensive coding practices and patterns for high Availability</li><li>
Experience in A/B testing and effective REST design for scalable web services architecture</li><li>
Familiarity with advanced machine learning architectures GANs, GRU, LSTMs, RNNs, CNNs, style transfer</li></ul><p><b><br>
Minimum Education:</b></p><ul><li>
The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.</li></ul><p><b><br>
Preferred Education:</b></p><ul><li>
No additional education</li></ul><p><b><br>
Minimum Years of Work Experience:</b></p><ul><li>
3</li></ul><p><b><br>
Preferred Years of Work Experience:</b></p><ul><li>
No additional years of experience</li></ul><p><b><br>
Minimum Leadership Experience:</b></p><ul><li>
None</li></ul><p><b><br>
Preferred Leadership Experience:</b></p><ul><li>
None</li></ul><p><b><br>
Certifications:</b></p><ul><li>
None</li></ul><p><b><br>
Competencies:</b></p><ul><li>
Global Perspective</li><li>
Manages Ambiguity</li><li>
Nimble Learning</li><li>
Self-Development</li><li>
Collaborates</li><li>
Cultivates Innovation</li><li>
Situational Adaptability</li><li>
Communicates Effectively</li><li>
Drives Results</li><li>
Interpersonal Savvy</li></ul></div><p></p>

Staff Machine Learning Engineer (Remote)

Powerplan

<div>Overview:
<p>
The Senior AI/ML Engineer will modernize and scale the company&rsquo;s enterprise data and AI platform by designing AI-ready data models, operationalizing ML systems, and enabling natural-language analytics through Databricks Genie or equivalent AI tooling.</p><p>
This role exists to shift the organization from dashboard-driven analytics to AI-powered decision intelligence at enterprise scale.</p>
Responsibilities:
<p><b>
Performance Objectives</b></p><p></p><p><b><br>
Modernize and Operationalize the Analytics Data Platform</b></p><p>
Within 6&ndash;9 months, design and implement a scalable medallion-based architecture (Bronze/Silver/Gold) in Databricks or Snowflake that supports AI-ready datasets, improves query performance by 30%, and reduces data reliability incidents by 40%.</p><p><b>
Subtasks:</b></p><ul><li>
Redesign analytical data models for AI/ML consumption</li><li>
Implement governance using Unity Catalog or Snowflake controls</li><li>
Optimize distributed compute performance</li><li>
Establish monitoring and quality validation checkpoints</li></ul><p></p><p><b><br>
Enable AI-Ready Data Modeling &amp; Governance</b></p><p>
Within 6 months, establish semantic models and metadata standards that enable business-facing AI querying with 95% data trust rating from stakeholders.</p><p><b>
Subtasks:</b></p><ul><li>
Standardize schema design for ML and GenAI workloads</li><li>
Align business definitions with governed datasets</li><li>
Implement lineage and access controls</li><li>
Reduce duplicate or conflicting metric definitions</li></ul><p></p><p><b><br>
Build and Deploy Production-Grade ML Pipelines</b></p><p>
Within 9&ndash;12 months, implement reusable ML lifecycle pipelines (experimentation training evaluation deployment) that reduce time-to-production for ML models by 50%.</p><p><b>
Subtasks:</b></p><ul><li>
Standardize MLflow/Feature Store workflows</li><li>
Implement CI/CD for ML</li><li>
Improve model observability and drift monitoring</li><li>
Establish model documentation standards</li></ul><p></p><p><b><br>
Implement Natural Language AI Analytics (Databricks Genie Enablement)</b></p><p>
Within 6 months, deploy and optimize Databricks Genie (or equivalent AI query interface) enabling business users to generate accurate plain-language insights with 80% adoption across target user groups.</p><p><b>
Subtasks:</b></p><ul><li>
Translate business questions into semantic AI-ready datasets</li><li>
Improve response accuracy through model + metadata tuning</li><li>
Partner with Product on use-case prioritization</li><li>
Track and improve AI query accuracy and user engagement</li></ul><p></p><p><b><br>
Democratize AI Across Business Teams</b></p><p>
Within 12 months, embed AI-driven analytics into at least 3 core business workflows, demonstrating measurable business impact (e.g., cost reduction, revenue lift, or decision cycle time improvement).</p><p><b>
Subtasks:</b></p><ul><li>
Identify high-value AI use cases</li><li>
Collaborate cross-functionally</li><li>
Deliver production-ready AI solutions</li><li>
Document business ROI outcomes</li></ul><p></p><p><b><br>
Establish Enterprise AI Platform Standards</b></p><p>
Within 12 months, define and institutionalize architectural standards, best practices, and governance frameworks adopted across Engineering and Analytics teams.</p><p><b>
Subtasks:</b></p><ul><li>
Publish architecture reference patterns</li><li>
Lead design reviews</li><li>
Mentor engineers</li><li>
Influence long-term AI strategy</li></ul><p></p><p><b><br>
Success Metrics Summary</b></p><ul><li>
30%+ performance improvement in analytics workloads</li><li>
40%+ reduction in data quality incidents</li><li>
50% reduction in ML deployment cycle time</li><li>
80% Genie adoption in target group</li><li>
3+ AI use cases with measurable ROI</li><li><ul><li>95% stakeholder trust in AI-generated insights</li></ul></li></ul>
Qualifications:
<p><b>
Growth &amp; Career Move</b></p><p>
This is a high-impact platform leadership role enabling enterprise AI transformation. The individual will shape architecture standards, influence executive AI strategy, and lead the shift from traditional BI to AI-powered decision intelligence.</p><p><b>
Required Qualifications</b></p><ul><li>
10+ years of experience in <b>Data Analytics</b>, <b>Data Engineering, ML Engineering, or AI Engineering</b></li><li>
Strong hands-on experience with <b>Databricks or Snowflake</b> in production environments</li><li>
Expertise in <b>SQL</b>, <b>Python</b>, and distributed data processing (Spark preferred)</li><li>
Strong understanding of <b>data modeling for analytics and AI</b></li><li>
Experience building and deploying <b>ML models</b> in real-world systems</li><li>
Familiarity with <b>LLMs, GenAI concepts, and AI-assisted analytics</b></li><li>
Experience with ML lifecycle tools (MLflow, Feature Stores, CI/CD for ML)</li></ul><div></div><div><b><br>
Preferred Qualifications</b></div><ul><li>
Direct experience with <b>Databricks Genie</b> or AI-powered BI tools</li><li>
Experience with <b>Unity Catalog, Delta Live Tables</b>, or Snowflake governance features</li><li>
Exposure to <b>Azure, AWS, or GCP</b> cloud platforms</li><li>
Experience working in regulated or enterprise SaaS environments</li><li>
Ability to explain complex technical concepts to non-technical stakeholders</li></ul><div></div><div><b><br>
What Success Looks Like in This Role</b></div><ul><li>
Business users can ask questions in plain English and get <b>trusted, accurate insights</b></li><li>
Data models are <b>AI-ready, scalable, and well-governed</b></li><li>
ML models move smoothly from experimentation to production</li><li>
Databricks Genie adoption grows with measurable business impact</li><li>
AI is embedded into analytics not bolted on</li></ul><div></div><div><b><br>
Why Join Us</b></div><ul><li>
Work on <b>real AI/ML problems at enterprise scale</b></li><li>
Influence the evolution of a modern <b>data + AI platform</b></li><li>
Partner with senior leaders shaping the company&rsquo;s AI-first future</li><li>
Build systems that turn data into decisions not dashboards</li></ul><div><b>
PowerPlan is an EOE</b></div><div>
Applicant Privacy Notice</div><div></div><p><br>
Please note that this is a hybrid role that involves a combination of onsite work from our corporate office as well as work from home. While we strive to accommodate flexible working arrangements when sensible, there will be times when onsite work is required. This could include scheduled office days, team meetings, client meetings, or special events.</p></div>

Senior Databricks AI Engineer

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