senior software engineer analytics

BillGO, Inc.

<div>Senior AI Data Analytics Engineer
BillGO is building the next generation of payments &mdash; an intelligent network that helps small businesses get paid faster, operate leaner, and grow with confidence. The Senior AI Data Analytics Engineer sets the technical direction for BillGO's data and AI architecture, turning payments data into reliable, scalable, and intelligent products the rest of the organization builds on. Reporting to the VP, Data Office, this role sits at the intersection of data engineering, analytics, AI/ML, and the business. It's an individual-contributor role with no direct reports &mdash; leadership is exercised through architecture, standards, and mentorship, not people management. Success is measured by the reliability, reuse, and trustworthiness of BillGO's data and AI products, not the volume of models or dashboards produced.<div>
</div>Why This Role Matters
BillGO's future runs on trustworthy data, and this role owns making sure it stays that way as the company scales. As the architect of the data models, semantic layers, and AI/RAG patterns that Product, Finance, Risk, and Operations all build on, this person turns scattered payments data into a single source of truth - while setting the validation standards that keep AI-generated insights accurate before they ever reach a decision-maker. It's an individual contributor role with outsized reach: get it right, and BillGO moves faster with more confidence - faster reconciliation, fewer fraud losses, and self-service, AI-powered insight in the hands of every team instead of just a few.
 What You&rsquo;ll Do
Data &amp; AI Architecture<ul><li>
Own the architecture and roadmap for scalable data models covering customers, payments, transactions, settlements, and financial reporting</li><li>
Architect solutions across Snowflake, AWS RDS, and AWS DynamoDB, integrating sources from AWS S3</li><li>
Lead the design of data dictionaries, semantic layers, and data catalogs that power both human and AI-driven analytics</li></ul>
Data Quality, Governance &amp; Standards<ul><li>
Set and evangelize engineering standards, patterns, and best practices, and drive their adoption across the organization</li><li>
Establish frameworks for data quality and integrity through testing, monitoring, and documentation</li><li>
Support regulatory and financial reporting needs &mdash; reconciliation, audit readiness &mdash; with accurate, well-governed data</li></ul>
Business Partnership &amp; Enablement<ul><li>
Partner with senior leaders across Product, Finance, Risk, and Operations to define key metrics and enable insights, dashboards, and predictive models</li><li>
Translate ambiguous business strategy into data and AI solutions that scale with company growth</li><li>
Put AI-powered, self-service insights in the hands of every team</li></ul>
Technical Leadership &amp; Mentorship<ul><li>
Set technical direction that improves visibility into payment performance and revenue drivers</li><li>
Mentor and coach engineers through design reviews, pairing, and code review</li><li>
Coach the team on using AI coding and analytics assistants to accelerate development and documentation</li><li>How You'll Use AI</li></ul>
This role treats AI as core infrastructure, not a side project. You'll apply generative AI and large language models (e.g., Claude) to accelerate data transformation, documentation, and metric definition, and to enable natural-language access to enterprise data. You'll architect retrieval-augmented generation (RAG) and semantic search over enterprise data so trusted datasets are easily discoverable and queryable by both humans and AI systems. You'll design, build, and operationalize AI/ML workflows &mdash; from feature engineering to LLM-powered pipelines &mdash; that turn analytics into predictions and automation. And because AI-generated insight is only as good as its validation, you'll establish the responsible AI practices &mdash; around bias, hallucination, and data privacy &mdash; that ensure AI outputs are checked before they influence a financial decision. You'll also coach the broader team on using AI coding and analytics assistants to work faster and document better.
 What You Bring<ul><li>
5+ years in analytics engineering, data analytics, or data engineering, including senior or lead responsibilities</li><li>
Expert SQL and data analytics skills, with proven ability to model complex datasets (fact/dimension modeling, star schemas) and design data architecture end to end</li><li>
Deep experience with data warehousing (Snowflake) and transformation frameworks like Coalesce, including establishing team conventions</li><li>
Experience building and owning metrics layers or semantic models used across multiple teams</li><li>
Strong command of ELT pipelines, data orchestration, and Python for data processing and automation</li><li>
Extensive hands-on experience applying generative AI and LLMs to real data and analytics problems in production</li><li>
Strong experience with RAG, embeddings, and vector databases, plus a solid ML and MLOps foundation</li><li>
A track record of technical leadership and mentorship, with a critical eye for data accuracy and AI-generated results</li><li>
Payments, fintech, financial services, or enterprise SaaS experience strongly preferred</li><li>
Skill at influencing and communicating with senior technical and non-technical stakeholders</li><li>
Nice to have: advanced data science/ML experience, LLM fine-tuning or benchmarking, agentic AI workflows, event-driven or streaming architectures, and hands-on knowledge of payments concepts like authorization/settlement, interchange, chargebacks, and reconciliation.</li></ul>
 Compensation<div>
</div>We offer a competitive executive compensation package, including:<ul><li>
Base salary ($132,800 - $196,500)</li><li>
Performance incentive</li><li>
Equity opportunities
</li><li>Comprehensive health, retirement, and lifestyle benefits</li></ul>
This role is about more than compensation, it&rsquo;s about the opportunity to transform how small businesses thrive in the digital economy.</div>

Senior AI Data Analytics Engineer

Datamatics Global Services Ltd

<div><h1 class="jobSectionHeader">Job Description: Analytics &amp; Transformation Engineer</h1>
Job Title: Analytics &amp; Transformation Engineer 
Experience: 3&ndash;11 Years 
Location: Riyadh - Onsite 
Employment Type: Full-Time<h2 class="jobSectionHeader">
Job Overview</h2>
We are seeking an experienced Analytics &amp; Transformation Engineer with 3&ndash;11 years of experience to drive data-driven transformation initiatives through advanced analytics, reporting, measurement frameworks, and business intelligence solutions. The ideal candidate will have expertise in dashboard development, semantic modeling, behavioral analytics, experimentation, and analytics implementation processes. This role requires strong analytical thinking and the ability to translate business objectives into measurable data solutions.<h2 class="jobSectionHeader">
Key Responsibilities</h2><ul><li>
Design and develop scalable analytics solutions to support business transformation initiatives.</li><li>
Build executive dashboards, reports, and analytical models to enable data-driven decision-making.</li><li>
Develop and maintain semantic models, metrics frameworks, and reporting standards.</li><li>
Perform behavioral analytics to understand user journeys, engagement patterns, and business performance.</li><li>
Define and implement event tracking strategies, analytics taxonomies, and measurement frameworks.</li><li>
Collaborate with product, engineering, marketing, and business teams to establish data-driven processes.</li><li>
Perform tracking implementation QA and ensure accuracy of analytics data collection.</li><li>
Conduct A/B testing analysis and evaluate the impact of product and business changes.</li><li>
Perform post-launch transaction analysis and ensure analytics readiness for new initiatives.</li><li>
Identify opportunities for process optimization and business improvement through data insights.</li></ul><h2 class="jobSectionHeader">
Required Technical Skills</h2><h3 class="jobSectionHeader">
Business Intelligence &amp; Visualization</h3><ul><li>
Hands-on experience with Power BI or Tableau or Looker for dashboard creation and analytics reporting.</li><li>
Experience developing interactive dashboards, KPI reporting, and executive-level visualizations.</li></ul><h3 class="jobSectionHeader">
Data Modeling &amp; Analytics Engineering</h3><ul><li>
Strong experience with SQL and dbt for data transformation and analytics workflows.</li><li>
Experience designing and maintaining semantic models and reusable analytical datasets.</li><li>
Understanding of data modeling concepts, metrics definitions, and reporting frameworks.</li></ul><h3 class="jobSectionHeader">
Product &amp; Behavioral Analytics</h3><ul><li>
Experience with Mixpanel or Amplitude or Google Analytics or Hotjar for user behavior analysis.</li><li>
Strong understanding of behavioral analytics, user journey tracking, and engagement measurement.</li><li>
Experience defining metrics, event taxonomy planning, and tracking implementation QA.</li></ul><h3 class="jobSectionHeader">
Experimentation &amp; Measurement</h3><ul><li>
Experience designing and analyzing A/B testing initiatives.</li><li>
Ability to measure business impact through controlled experiments and analytical insights.</li><li>
Experience with post-launch analysis, transaction analysis, and performance tracking.</li></ul><h3 class="jobSectionHeader">
Reporting &amp; Productivity Tools</h3><ul><li>
Advanced proficiency in Microsoft Excel for analysis, reporting, and data validation.</li><li>
Experience working with analytics methodologies and comparable tools/platforms.</li></ul><h2 class="jobSectionHeader">
Qualifications</h2><ul><li>
Bachelor's degree in Data Analytics, Computer Science, Information Systems, Business Analytics, Statistics, or a related field.</li><li>
3&ndash;11 years of professional experience in Analytics, Business Intelligence, Data Transformation, or Product Analytics.</li><li>
Strong analytical, problem-solving, and communication skills.</li><li>
Ability to work with technical and non-technical stakeholders.</li><li>
Experience working in Agile/Scrum environments.</li></ul><h2 class="jobSectionHeader">
Preferred Skills</h2><ul><li>
Experience supporting digital transformation and product analytics initiatives.</li><li>
Knowledge of cloud data platforms such as AWS, Azure, or Google Cloud Platform.</li><li>
Familiarity with data governance, analytics standards, and measurement frameworks.</li><li>
Experience working with large-scale datasets and enterprise reporting environments.</li><li>
Certifications in analytics, BI tools, or cloud technologies are a plus.</li></ul><h2 class="jobSectionHeader">
Key Technology Stack</h2><ul><li>
Business Intelligence: Power BI or Tableau or Looker</li><li>
Analytics Engineering: dbt and SQL</li><li>
Data Modeling: Semantic Models and Metrics Frameworks</li><li>
Behavioral Analytics: Mixpanel or Amplitude or Google Analytics or Hotjar</li><li>
Product Analytics: Behavioral Analytics and Event Taxonomy Planning and A/B Testing</li><li>
Reporting &amp; Analysis: Excel and Dashboard Creation</li><li>
Analytics Operations: Tracking Implementation QA and Post-Launch Transaction Analysis Readiness</li><li>
Comparable Tools &amp; Methods: Similar analytics, BI, and transformation platforms as required by business needs</li></ul>
YIaTsfUsPM</div>

Analytics & Transformation Engineer

Infomineo

<div>
 
 
 About us
 
 
 
 Infomineo is a pioneering global AI-enhanced research company that transforms how businesses access, analyze, and act on critical intelligence. We&rsquo;ve evolved from traditional business research outsourcing to become the strategic partner that combines cutting-edge artificial intelligence with deep human expertise. We offer 3 services to our global clients (leading consulting companies, Fortune 500 companies, and government entities): AI and Data Advisory, Next-Gen Insights and Resource Scaling. This is made possible by relying on 3 pillars of excellence:
 
 
 
 
 <ol>
 <li>
 350+ industry experts spread across 5 offices (Cairo, Casablanca, Mexico City, Dubai, Barcelona).
 </li>
 <li>
 Our proprietary AI orchestrator.
 </li>
 <li>
 Extensive knowledge assets combining 500,000+ delivered case studies and database subscriptions.
 </li>
 </ol>
 
 
 
 
 Ready to kick start your career with us?
 
 
 
 Why Infomineo? Here&rsquo;s what sets us apart:
 
 
 <ul>
 <li>
 
 Shape the Future of Business Insights:
 
 You will be at the forefront, leading the design and implementation of AI-driven solutions that automate tasks and drive efficiency across our entire service spectrum (Business Research, Content, Design, and Data Analytics).
 </li>
 <li>
 
 Work with Global Leaders:
 
 Our clients are industry leaders &mdash; Fortune 500s, top consultancies, governments, and NGOs. You will take ownership of delivering technical solutions that directly support their success.
 </li>
 <li>
 
 Lead in AI &amp; Technology:
 
 We foster continuous learning and technical excellence. You will stay ahead of the latest advancements in AI and software engineering, and actively drive innovation across the team.
 </li>
 <li>
 
 Thrive in a Collaborative Culture:
 
 We value intellectual curiosity, leadership, and a can-do attitude. You will be encouraged to mentor others, contribute strategic ideas, and make a lasting impact on the company&rsquo;s growth.
 </li>
 </ul>
 
 
 
 
 
 About this role:
 
 
 
 We are seeking an experienced and technically strong individual to join us as
 
 Senior AI Software Engineer.
 
 In this role, you will take ownership of designing, developing, and deploying AI-powered data products and analytical applications that serve our internal teams and global clients. You will lead data science and AI initiatives, define best practices for applied AI and analytical solution development, and collaborate closely with engineering, product, and business stakeholders. While the role is primarily data science and AI-focused, you will also leverage your full-stack development background to build production-ready applications, integrate AI capabilities, and support cloud-based deployment.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 Data Science, AI &amp; Applied R&amp;D:
 
 
 <ul>
 <li>
 Lead the design and development of AI-powered analytical solutions, data products, and intelligent applications that solve complex business problems.
 </li>
 <li>
 Translate business and client requirements into data science approaches, AI workflows, and scalable technical solutions.
 </li>
 <li>
 Design, prototype, and productionize machine learning, LLM, and generative AI solutions with a focus on business value, reliability, and usability.
 </li>
 <li>
 Own the architecture of Retrieval-Augmented Generation (RAG) pipelines, including document processing, vectorization, semantic search, evaluation, and query optimization for enterprise use cases.
 </li>
 <li>
 Design and implement complex AI-powered features by integrating LLM APIs and services using frameworks such as LangChain or equivalent, with a focus on reliability, accuracy, and performance in production.
 </li>
 <li>
 Design, implement, and maintain Model Context Protocol (MCP) integrations to connect AI models with external tools, APIs, and data sources, enabling context-aware and extensible AI solutions.
 </li>
 <li>
 Develop evaluation frameworks, monitoring approaches, and observability practices for LLM-powered systems to ensure quality, transparency, and continuous improvement.
 </li>
 <li>
 Apply advanced prompt engineering, embedding strategies, and vector database management techniques to improve the performance of AI solutions.
 </li>
 <li>
 Integrate AI outputs into analytical workflows, dashboards, reporting tools, and client delivery pipelines.
 </li>
 </ul>
 
 
 
 
 
 Full-Stack Application Development:
 
 
 <ul>
 <li>
 Design and contribute to the development of production-grade AI and data applications, primarily using Python and backend frameworks such as FastAPI.
 </li>
 <li>
 Build or support frontend interfaces using modern frameworks such as React, Next.js, or Vue to make AI and data products accessible to business users and clients.
 </li>
 <li>
 Collaborate with software engineers to define scalable application architectures, API standards, and integration patterns.
 </li>
 <li>
 Develop and maintain REST API integrations with third-party AI services, enterprise SaaS platforms, internal tools, and external data sources.
 </li>
 <li>
 Ensure that data science prototypes are translated into maintainable, secure, and scalable production solutions.
 </li>
 <li>
 Participate in code reviews, define technical best practices, and contribute to a high-quality engineering and data science culture.
 </li>
 </ul>
 
 
 
 
 
 Cloud, Deployment &amp; MLOps:
 
 
 <ul>
 <li>
 Support the containerization and cloud deployment of AI and data applications, preferably on Google Cloud Platform using GKE and Artifact Registry, while remaining adaptable to other cloud environments.
 </li>
 <li>
 Design and maintain CI/CD pipelines using GitHub Actions or equivalent tools to ensure reliable and repeatable releases.
 </li>
 <li>
 Apply MLOps and LLMOps practices to manage experimentation, deployment, monitoring, and continuous improvement of AI systems.
 </li>
 <li>
 Collaborate with engineering and infrastructure teams to ensure the reliability, scalability, and performance of production environments.
 </li>
 <li>
 Proactively identify performance bottlenecks in AI workflows, data pipelines, application layers, and infrastructure.
 </li>
 </ul>
 
 
 
 
 
 Technical Leadership &amp; Collaboration:
 
 
 <ul>
 <li>
 Lead applied AI and data science initiatives from discovery and prototyping through production deployment.
 </li>
 <li>
 Mentor junior data scientists, AI engineers, and developers on data science methods, AI integration, coding practices, and production readiness.
 </li>
 <li>
 Work closely with product teams, consultants, analysts, and non-technical stakeholders to ensure solutions are aligned with business needs.
 </li>
 <li>
 Define standards and best practices for AI solution design, evaluation, documentation, and delivery.
 </li>
 <li>
 Communicate complex technical concepts clearly to both technical and non-technical audiences.
 </li>
 </ul>
 
 
 
 
 
 Qualifications:
 
 
 <ul>
 <li>
 4 to 6 years of experience in data science, AI development, applied machine learning, or related technical roles, with hands-on experience delivering production-grade AI or data products.
 </li>
 <li>
 Strong proficiency in Python, with experience using data science, machine learning, and AI libraries and frameworks.
 </li>
 <li>
 Solid full-stack development background, including experience with backend frameworks such as FastAPI and modern frontend frameworks such as React, Next.js, or Vue.
 </li>
 <li>
 Deep understanding of LLMs, RAG architectures, generative AI workflows, and production-grade AI service integration, including tools such as OpenAI, Gemini, LangChain, or equivalent.
 </li>
 <li>
 Proven experience designing and implementing Model Context Protocol (MCP) integrations to connect AI models with external tools, APIs, and enterprise data sources.
 </li>
 <li>
 Experience building analytical workflows, dashboards, data pipelines, or AI-powered decision-support tools in a client delivery or enterprise context.
 </li>
 <li>
 Hands-on experience with Docker and cloud deployment on at least one major cloud platform such as GCP, AWS, Azure, or equivalent.
 </li>
 <li>
 Familiarity with container orchestration, artifact management, CI/CD pipelines, GitHub Actions, GitOps workflows, and branching strategies.
 </li>
 <li>
 Strong understanding of LLM observability, AI evaluation, performance monitoring, and production reliability practices.
 </li>
 <li>
 Demonstrated ability to lead technical initiatives, mentor junior team members, and collaborate effectively with product teams and business stakeholders.
 </li>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Computer Science, Software Engineering, Statistics, Applied Mathematics, or a related field.
 </li>
 </ul>
 
 
 
 
 
 Preferred Skills:
 
 
 <ul>
 <li>
 Experience with agentic AI frameworks such as LangGraph or similar orchestration tools for building multi-step AI workflows.
 </li>
 <li>
 Knowledge of advanced prompt engineering, vector database management, embedding model optimization, and AI evaluation techniques.
 </li>
 <li>
 Experience with MLOps or LLMOps practices, including experiment tracking, model monitoring, and AI quality evaluation.
 </li>
 <li>
 Experience with Infrastructure as Code tools such as Terraform or Pulumi.
 </li>
 <li>
 Experience designing data models, analytical pipelines, or BI/dashboard solutions.
 </li>
 <li>
 Relevant certifications such as Google Cloud Professional Data Engineer, Google Cloud Professional Machine Learning Engineer, Google Cloud Professional Developer, or similar cloud and AI credentials.
 </li>
 </ul>
 
 
 
 
 
 What we offer:
 
 
 <ul>
 <li>
 A competitive compensation and benefits package.
 </li>
 <li>
 The opportunity to lead AI and technology initiatives with real global impact.
 </li>
 <li>
 A dynamic and supportive work environment that values leadership, innovation, and your contributions.
 </li>
 <li>
 Continuous learning and professional development opportunities to propel your career forward in AI and software engineering.
 </li>
 </ul>
 
 
 
 
 
 Application Process:
 
 
 
 Candidates are invited to submit a resume, cover letter, and any relevant portfolio or GitHub links showcasing their experience in web application development, AI integration, and cloud deployment. Shortlisted candidates will undergo a technical assessment and interview to demonstrate their skills and technical leadership capabilities.
 
 
 
 
 
 
 Infomineo: Where brilliant minds meet to shape the future of business.
 
 
 
 
</div>

AI & Analytics - Sr. Software Engineer with AI Background - Cairo

CVS Health

<div>We&rsquo;re building a world of health around every individual &mdash; shaping a more connected, convenient and compassionate health experience. At CVS Health&reg;, you&rsquo;ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger &ndash; helping to simplify health care one person, one family and one community at a time.<div>
Position Summary 
We are seeking a skilled and analytical Senior Product Analyst to lead the development and execution of a data-driven product roadmap. The ideal candidate will have a deep understanding of product analytics, strong problem-solving skills, and experience working with cross-functional teams to support strategic initiatives. 
 
As a Senior Product Analytics Associate, you will work closely with cross-functional teams including engineering, product, and clinical operations. 
 
Roles and Responsibilities:</div><ul><li>
Define, track, and report on product metrics including performance and profitability</li><li>
Build and maintain robust data transformation models using dbt (or similar frameworks like Dataform or SQL-based ETL tools) to ensure analytics-ready datasets</li><li>
Build and maintain Power BI dashboards to track product health and monitor the success of product initiatives</li><li>
Design and interpret A/B tests; when A/B testing is not feasible, apply causal inference methods (e.g., Diff-in-Diff, Propensity Score Matching) to determine product efficacy.</li><li>
Develop ROI projections for analytics projects to prioritize deliverables by business impact</li><li>
Tell compelling stories through data, articulating technical information to a non-technical audience</li></ul><div> 

Basic Qualifications:</div><ul><li>
Bachelor&rsquo;s degree in a technical field (Statistics, Data Science, CS, Engineering, or related)</li><li>
5+ years of experience in a technical product analytics or data science role</li><li>
Experience with dbt (Data Build Tool) or similar analytics engineering tools, including version control (Git)</li><li>
Experience with A/B testing, funnel analysis, and statistical methods (regression, clustering, or predictive modeling).</li><li>
Advanced proficiency in SQL and experience with Python or R</li><li>
Experience working with data engineering teams to develop data pipelines</li></ul><div> 

Preferred Qualifications:</div><ul><li>
Power BI experience</li><li>
Familiarity with advanced causal inference techniques (e.g., instrumental variables)</li></ul>
Anticipated Weekly Hours
40
Time Type
Full time
Pay Range
The typical pay range for this role is:
$92,700.00 - $185,400.00
This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. 
Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.
Great benefits for great people
We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families. 
This full‑time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well‑being of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility. 
Additional details about available benefits are provided during the application process and on Benefits Moments. 
We anticipate the application window for this opening will close on: 07/25/2026
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.</div>

Sr Product Analytics Associate

talabat

<div>
 Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat&rsquo;s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.
 
 
 We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.
 
 
 Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.
 
 
 
 Job Description
 
 
 
 As the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.
 
 
 As a n Analytics Engineer, you will be responsible for transforming raw data into well-structured, reliable, and accessible data models that enable analysts, data scientists, and business stakeholders to make informed decisions. You will work closely with data engineers to build scalable data pipelines and collaborate with analysts to ensure data is actionable and insightful.
 
 
 <ul>
 <li>
 Design, build, and maintain clean, efficient, and scalable data models in SQL and dbt. Optimize query performance and data processing efficiency.
 </li>
 <li>
 Ensure data is structured to support self-service analytics and business intelligence.
 </li>
 <li>
 Work closely with data engineers to define data requirements and enhance ETL pipelines.
 </li>
 <li>
 Partner with product analysts, data scientists, and business teams to ensure data meets analytical and reporting needs.
 </li>
 <li>
 Implement and enforce data quality best practices to ensure accuracy and consistency.
 </li>
 <li>
 Develop and maintain data transformation workflows using dbt, SQL, and cloud-based data platforms. Automate data validation and reporting processes.
 </li>
 <li>
 Monitor data integrity and troubleshoot data issues proactively. Advocate for best practices in documentation, testing, and version control.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.
 </li>
 <li>
 Strong proficiency in Python, SQL and experience with dbt for data modeling.
 </li>
 <li>
 Experience working with cloud-based data warehouses (e.g., Snowflake, BigQuery, GCP, Redshift).
 </li>
 <li>
 Familiarity with version control (Git) and CI/CD practices for data workflows.
 </li>
 <li>
 Understanding of data engineering principles, including ETL/ELT processes.
 </li>
 </ul>
</div>

Analytics Engineer II

Gallup

<div>
 
 Shape product road maps and strategies with data-driven analytics and insights.
 
 
 
 As a senior/staff data scientist focused on product analytics for our Technology team, you&rsquo;ll work with product managers, engineers and designers to define success, validate hypotheses, and measure user behavior and product performance.
 
 
 We&rsquo;re looking for self-driven, curious analytics partners who thrive in ambiguity, learn continually and help teams accelerate decision-making.
 
 
 At Gallup, our analytics reflect what the world is thinking, empower millions of people to thrive using their strengths, and help leaders create exceptional workplaces. If you want your work to influence products that bring that mission to life, we&rsquo;d love to hear from you.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Partner with product teams early in discovery, road map discussions and launch planning to turn goals into measurable outcomes
 </li>
 <li>
 Define and govern success metrics by building trusted metric definitions, dashboards and data models that enable self-serve decision-making
 </li>
 <li>
 Design and evaluate product experiments and analyses to assess the impact of new features, onboarding changes and product improvements
 </li>
 <li>
 Serve as a thought partner to product managers by pressure-testing hypotheses before implementation and confirming whether outcomes match expectations after launch
 </li>
 <li>
 Translate analysis into action by communicating what happened; why it happened; and what stakeholders, leaders and partners should do next
 </li>
 <li>
 Improve analytics readiness by partnering with data platform and engineering teams on instrumentation, extraction, processing and modeling to ensure reliable, analysis-ready data
 </li>
 <li>
 Scale product analytics at Gallup by contributing to best practices, frameworks and repeatable ways of working
 
 
 </li>
 </ul>
 
 What Makes You Stand Out
 
 
 
 <ul>
 <li>
 Proactive problem-solving: You anticipate issues and opportunities in the data, translate analysis into action, and rapidly drive improvements to the user experience.
 </li>
 <li>
 Persistent resourcefulness: You independently create clarity from ambiguity, connecting distributed data, validating quality and delivering insights without relying on fully defined systems.
 </li>
 <li>
 Trusted product partnership: You collaborate closely with product, engineering, design, research and operations teams to solve complex problems, and confidently deliver constructive, data-backed recommendations.
 </li>
 <li>
 Experimentation judgment: You know when A/B tests are feasible and when they aren&rsquo;t, and you can choose rigorous alternatives to answer product questions.
 </li>
 <li>
 Expert data storytelling: You explain trends, uncertainty and limitations in plain language and deliver recommendations people can act on.
 </li>
 <li>
 Curious culture-builder: You experiment with emerging tools, including AI, to improve team effectiveness and actively build data fluency so partners can confidently navigate metrics and insights.
 
 
 </li>
 </ul>
 
 What You Need
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in computer science, computer engineering, mathematics, statistics or a related field, or equivalent experience, required
 </li>
 <li>
 At least five years of experience in product analytics or data science required; eight or more years of experience preferred
 </li>
 <li>
 At least five years of experience with SQL for analysis in modern data environments required
 </li>
 <li>
 At least five years of experience with Python and data science tool kits (e.g., pandas) required
 </li>
 <li>
 Experience leading data-driven projects end to end, including defining metrics, designing experiments/analyses and communicating actionable insights required
 </li>
 <li>
 Strong statistical intuition, analytical rigor, and experience validating data and performing quality checks required
 </li>
 <li>
 High fluency with MPP databases such as Snowflake or Redshift required
 </li>
 <li>
 Some data engineering or instrumentation experience (pipelines, event tracking, modeling) preferred
 </li>
 <li>
 A commitment to working on-site at Gallup&rsquo;s Omaha office at least three days per week required
 
 
 </li>
 </ul>
 
 About Gallup
 
 
 
 At Gallup, we change the world, one client at a time, through extraordinary analytics and advice on everything important facing humankind. Learn more about our work and life at Gallup.
 
 
 Gallup offers a robust benefits package that includes medical, dental, vision, life and other insurance options; a fully vested 401(k) retirement savings plan with company matching; an employee stock ownership program; family-building benefits; an employee assistance program; and various reimbursements and activities that enhance our associates&rsquo; wellbeing. We also offer an estimated annual salary range of $135,000-$180,000 for this role. Salaries are based on a variety of factors, including an individual&rsquo;s education, experience and skills.
 
 
 Gallup is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender identity, or any other legally protected basis, in accordance with applicable law.
 
 
 To review Gallup&rsquo;s Privacy Statement, please click this link: https://www.gallup.com/privacy. This privacy policy is meant to help you understand what information we collect, why we collect it, and how you can update, manage and delete your information. Your application and the information you provide will be processed and stored in the United States.
 
 
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