analytics engineer

True Classic

<div>True Classic is hiring a Data &amp; Analytics Engineer to partner in owning our data platform infrastructure and to serve as a key builder connecting our data warehouse to our AI, finance, and business stakeholder teams. This role will support core analytics engineering functions, ensuring clean, well-structured, and reliable data pipelines built to best practice standards.
This role is ideal for someone who is hands-on and technically rigorous, with a strong command of data engineering best practices &mdash; including pipeline design, data modeling, testing, and documentation &mdash; and can contribute meaningfully to a mid-build platform in a fast-paced, evolving environment.
All of True Classic&rsquo;s roles are global and omni-channel, leading designated areas of accountability across all product categories, countries, and sales and marketing channels. This role will have impact across DTC, retail, wholesale, marketplaces, and emerging channels, ensuring strategic alignment and executional rigor across the enterprise.<h2 class="jobSectionHeader">
Areas of Accountability</h2><h3 class="jobSectionHeader">
Extend &amp; Maintain the Data Platform</h3><ul><li>
Build and maintain dbt models following best practices for modularity, testing, documentation, and code quality</li><li>
Contribute to completion of open data model workstreams across inventory, media, and product functions</li><li>
Expand data source connectivity and pipeline coverage across marketing and fulfillment systems</li><li>
Maintain and improve ETL/ELT workflows via Daasity and BigQuery</li><li>
Help monitor and optimize cloud data infrastructure for cost and performance</li></ul><h3 class="jobSectionHeader">
Bridge Data to the Business</h3><ul><li>
Deploy and maintain Omni dashboards on top of BigQuery for cross-functional stakeholders</li><li>
Support business KPI tracking by structuring financial data for forecasting, cost modeling, and channel-level P&amp;L</li><li>
Contribute to predictive models for demand forecasting, inventory planning, and revenue projections</li><li>
Build and maintain the serving layer that the AI team queries &mdash; clean, modeled BigQuery tables in place of direct API calls</li></ul><h3 class="jobSectionHeader">
AI-Augmented Development</h3><ul><li>
Use AI coding tools (Claude Code, Cursor, Copilot) daily to write dbt models, debug pipelines, and accelerate development</li><li>
Collaborate with the AI team to ensure the warehouse serves their applications with clean inputs for automation, ML models, and real-time ops tools</li><li>
Identify opportunities where AI can automate data quality checks, anomaly detection, and pipeline monitoring</li></ul><h3 class="jobSectionHeader">
Cross Functional Collaboration</h3><ul><li>
Work with finance to ensure financial data structures support forecasting and P&amp;L reporting needs</li><li>
Partner with the AI team to ensure warehouse outputs support downstream automation and machine learning applications</li><li>
Work alongside merchandising, operations, and analytics stakeholders to translate business questions into reliable data models and visualizations</li></ul><h2 class="jobSectionHeader">
Qualifications</h2><ul><li>
4+ years of experience in data engineering or analytics engineering</li><li>
Strong understanding of data engineering best practices: pipeline design, data modeling, testing, and documentation</li><li>
Hands-on experience with dbt Cloud, Google BigQuery, and SaaS API pipeline development</li><li>
Strong SQL skills including joins, window functions, and CTEs</li><li>
Python proficiency for pipeline scripting, API integrations, and light modeling</li><li>
Familiarity with statistical modeling and predictive analytics (regression, time series)</li><li>
Comfortable working with non-technical stakeholders to translate business questions into data models and visualizations</li><li>
Proficiency with AI coding tools &mdash; daily use expected</li></ul><h2 class="jobSectionHeader">
Preferred Qualifications</h2><ul><li>
NetSuite or ERP experience</li><li>
Daasity, Shopify/Amazon data</li><li>
Marketing attribution platforms (Meta CAPI, Google Ads, Triple Whale),</li><li>
Omni/Looker, GitHub-based workflows</li></ul><h2 class="jobSectionHeader">
Workplace Arrangement</h2>
This role is on-site (5x week in office) based in Calabasas, CA.<h2 class="jobSectionHeader">
Compensation and Benefits</h2><h3 class="jobSectionHeader">
Compensation</h3><ul><li>
Competitive Salary + bonus</li></ul><h3 class="jobSectionHeader">
Time Off</h3><ul><li>
Unlimited PTO and sick time</li></ul><h3 class="jobSectionHeader">
Health &amp; Wellness</h3><ul><li>
Company-paid medical, dental, and vision insurance</li><li>
$100/month Health &amp; Wellness stipend</li><li>
Free Employee Assistance Program (EAP)</li></ul><h3 class="jobSectionHeader">
Work &amp; Growth Support</h3><ul><li>
$100/month Personal Workspace/Office stipend</li></ul><h3 class="jobSectionHeader">
Perks</h3><ul><li>
$1,000/year True Classic merchandise allowance</li><li>
401(k) plan with 3% company match</li></ul></div>

Data & Analytics Engineer

Cerebras Systems

<div><div><h2 class="jobSectionHeader">Location</h2>
Headquarters/Sunnyvale Office
</div><div><h2 class="jobSectionHeader">Employment Type</h2>
Full time
</div><div><h2 class="jobSectionHeader">Location Type</h2>
Hybrid
</div><div><h2 class="jobSectionHeader">Department</h2>
Hardware Departments</div></div>
 <div><div>Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
 
 
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
 
 
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Cerebras Systems Inc. has multiple openings for Hardware Analytics Engineer
Title: Hardware Analytics Engineer
Job Duties:
<ul><li>Design and optimize scalable data pipeline architectures for multi-terabyte hardware telemetry, reliability analytics, and performance optimization.
</li><li>Architect, develop, and optimize hyperscale data pipeline frameworks and ETL processes to aggregate, process, and analyze multi-terabyte hardware performance and telemetry streams, including utilization, power, thermal, acoustic, and reliability metrics across heterogeneous compute, storage, and AI server platforms, ensuring hardware performance compliance and operational reliability.
</li><li>Design and implement hardware performance analysis and anomaly detection systems using Python, SQL, Tableau, Hive, and Spark to forecast hardware failure curves, identify performance bottlenecks, and generate prescriptive recommendations for hardware and system optimization.
</li><li>Lead hardware characterization experiments and thermal/cooling A/B studies to evaluate operational envelopes, delivering validated strategies that reduce carbon footprint, improve water usage efficiency, and maintain or enhance system reliability.
</li><li>Engineer telemetry ingestion, monitoring, and visualization systems to provide real-time, high-fidelity hardware health data to hardware, firmware, and datacenter operations teams, enabling data-driven decision-making at scale.
</li><li>Define, operationalize, and maintain custom efficiency and reliability metrics; perform root cause analysis of systemic failures using large-scale statistical and machine learning methods; and deploy solutions that improve platform scalability, energy efficiency, and sustainability.
</li><li>Collaborate with cross-functional engineering teams to troubleshoot complex failures, isolate defective components, and implement systemic fixes across CPU, GPU, DRAM, PCIe, networking, and storage subsystems.
</li><li>Support the evolution and optimization of next-generation AI platforms and silicon products, including hardware subsystems (CPU, GPU, DRAM, PCIe, networking, and storage), to meet the performance, scalability, and efficiency demands of large language model training and inference workloads.
</li></ul>Minimum Requirements:
Master&rsquo;s degree or foreign equivalent degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field and 3 years of experience as Hardware Analytics Engineer, Hardware Engineer, Data Engineer, or a related occupation required.
Required Skills:
<ul><li>Large-scale data pipeline architecture and ETL, distributed data processing (Hive, Spark), and dashboard development;
</li><li>Python, SQL, Tableau, Linux, and automation scripting;
</li><li>Design, training, and deployment of machine learning models for hardware performance optimization and failure prediction;
</li><li>Predictive modeling, statistical analysis, A/B testing, anomaly detection, and data visualization in hardware reliability and performance; and
</li><li>Hardware analytics for compute, storage, and AI servers; power and thermal optimization; GPU burn-in efficiency optimization; and reliability modeling for AI hardware systems and components including CPU, GPU, DRAM, and SSD. 
</li></ul><div></div>Additional Information:
Employer&rsquo;s name: Cerebras Systems Inc.
Job site : 1237 E Arques Avenue, Sunnyvale, CA 94085
Telecommuting permitted
Salary Range: $213,675.00 per year to $225,000.00 per year
If you are interested in applying for this position, please apply online on this web page or mail resume to HR at Cerebras Systems Inc., 1237 E Arques Avenue, Sunnyvale, CA 94085. Please reference Job # 144 on resume or cover letter.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we&rsquo;ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
<div><ul><li>Build a breakthrough AI platform beyond the constraints of the GPU.
</li></ul><ul><li>Publish and open source their cutting-edge AI research.
</li></ul><ul><li>Work on one of the fastest AI supercomputers in the world.
</li></ul><ul><li>Enjoy job stability with startup vitality.
</li></ul><ul><li>Our simple, non-corporate work culture that respects individual beliefs.</li></ul></div> 

Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.</div></div>

Hardware Analytics Engineer

Wells Fargo

<div>Description
Title:Data Analytics Engineer
Location: Chandler, AZ
Duration: 104 W, 2 D
Work Engagement: W2
Work Schedule: Hybrid 3 days in office/2 days remote
Benefits on offer for this contract position: Health Insurance, Life insurance, 401K and Voluntary Benefits
Summary:
In this contingent resource assignment, you may: Consult on or participate in moderately complex initiatives and deliverables within Business Execution and contribute to large-scale planning related to Business Execution deliverables. Review and analyze moderately complex Business Execution challenges that require an in-depth evaluation of variable factors. Contribute to the resolution of moderately complex issues and consult with others to meet Business Execution deliverables while leveraging solid understanding of the function, policies, procedures, and compliance requirements. Collaborate with client personnel in Business Execution. Required Qualifications: Business Execution, Implementation, or Strategic Planning experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.
Key Requirements:<ul><li>Applicants must be authorized to work for ANY employer in the U.S. This position is not eligible for visa sponsorship.</li><li>Design and maintain Power BI dashboards that deliver actionable insights for technology, risk, and governance stakeholders.</li><li>Develop and optimize SQL queries for data extraction, analysis, validation, and reporting.</li><li>Automate data extraction, transformation, and reporting processes using Power Query and ETL methodologies.</li><li>Partner with stakeholders to gather requirements and translate business needs into effective technical solutions.</li><li>Analyze complex data sets to identify trends, risks, opportunities, and process improvements.</li><li>Create and manage user stories, requirements, and development activities within Jira for ServiceNow development.</li><li>Provide ongoing support, enhancements, and continuous improvement for reporting and analytics solutions.</li></ul><ul><li>
PowerBI development</li><li>
Github,</li><li>
SQL Query,</li><li>
Data visualization</li></ul></div>

Data Analytics Engineer (contract)

ANDHealth

<div><h2 class="jobSectionHeader">Analytics Engineer, Care Operations</h2>
Full Time &ndash; Exempt
Columbus, Ohio 
AndHealth is on a mission to radically improve access and outcomes for the most challenging
chronic health conditions, with the goal of making world-class specialty care accessible and affordable to all. We partner with health systems, community health centers, and independent practices to remove barriers to care to ensure all people have access to the care they deserve.
None of that happens without good data. Every model we build, every intervention we design, and every conversation our care teams have with a partner is only as strong as the data behind it. That's where you come in.
About the role
We're looking for an Analytics Engineer to be the dedicated data partner to our Care Delivery team &mdash; the people on the front lines of getting patients into care and keeping them there. You'll take raw clinical and operations data and turn it into something a care leader can actually use: a trusted number on a dashboard, a governed metric everyone agrees on, a model that surfaces a problem before it becomes a crisis.
This is an embedded data partner role that sits close to Care Delivery. You'll be just as comfortable deep in a dbt model or a gnarly SQL query as you are in a room with a VP, translating what the data means and what to do about it. If you like owning a domain end to end &mdash; from the metric definition in the semantic layer to the dashboard a leader checks every morning &mdash; this role is for you.
Impact
The dashboards and data products you build will directly shape how AndHealth delivers care to thousands of patients managing chronic, often life-altering conditions. When you catch a data quality issue before it reaches a report, you're protecting the integrity of decisions that affect real people's access to care. When you build the semantic layer that lets an analyst self-serve a trusted metric instead of waiting on you, you're multiplying the entire team's ability to act. This isn't dashboards for dashboards' sake &mdash; it's the infrastructure that lets Care Operations see what's working, fix what isn't, and prove the value we bring to the partners and patients who depend on us. 
 
What you'll do:<ul><li>
Translate business decisions into metrics &mdash; work with stakeholders to understand the decision they're trying to make, help them articulate what they need, and define the governed metric that answers it.</li><li>
Partner with stakeholders from several teams to generate actionable insights that improve AndHealth's value to our partners and patients.</li><li>
Build internal and external reporting and dashboards that visualize what's happening, why it's happening, and what we should do next across pharmacy and care operations.</li><li>
Develop the semantic layer in dbt &mdash; defining governed metric definitions, curated datasets, and self-service data products that analysts and stakeholders can consume directly.</li><li>
Partner with Data and Software Engineering as a key consumer of the raw data &mdash; flagging upstream data quality issues and gaps, and helping shape staging transformations so data arrives in a usable form.</li><li>
Build a thorough testing suite across the data platform: schema tests, data quality checks, anomaly detection, and SLA monitoring so stakeholders can trust what they see.</li><li>
Partner with the client management team to build the value story for quarterly business reviews.</li><li>
Become a domain expert in your assigned area (care operations), translating business logic into accurate, scalable dbt data models.</li><li>
Proactively identify data quality issues, gaps in coverage, and opportunities to improve the reliability and usability of the data platform.</li></ul> 
Education &amp; Licensure Requirements:<ul><li>
Bachelor's degree in Computer Science, Economics, Engineering, Mathematics, or a related quantitative field, or equivalent practical experience.</li></ul> 
Other Skills or Qualifications:<ul><li>
6+ years of data analysis or related experience with significant experience partnering directly with business stakeholders.</li><li>
Proven ability to turn ambiguous business questions into concrete, governed metric definitions &mdash; comfortable leading the discovery conversation with stakeholders rather than just executing a spec.</li><li>
Strong analytical instincts &mdash; able to interrogate data, identify anomalies, trace them to their source, and communicate findings clearly to technical and non-technical audiences.</li><li>
Strong SQL proficiency &mdash; complex queries, CTEs, window functions, and performance-optimized transformations across large datasets.</li><li>
Hands-on experience with dbt (Core or Cloud) &mdash; preferred.</li><li>
Comfortable working within a dimensionally modeled warehouse &mdash; facts and dimensions, mart layers, and why transformations are separated into staging, intermediate, and mart layers &mdash; even if you haven't owned that architecture from the ground up.</li><li>
Experience creating reporting systems and visualizations; advanced experience with Excel and other data systems.</li><li>
Comfort working alongside ETL/ELT pipelines and partnering with data or software engineers on ingestion.</li><li>
Experience with a BI tool (Omni, Looker, Metabase, or similar), especially defining governed metrics and data products &mdash; preferred.</li><li>
Familiarity with healthcare data (clinical, pharmacy, billing, or claims from EHRs, TPAs, or pharmacy operating systems) &mdash; preferred.</li><li>
Advanced data modeling experience &mdash; designing non-trivial dbt/SQL models that encode real business logic.</li><li>
Experience with R or Python or another scripting language in data analysis work &mdash; preferred.</li><li>
Comfort working in ambiguous, fast-moving environments with competing priorities.</li></ul> 
Here's what we'd like to offer you:<ul><li>
Equal investment and support for our people and patients.</li><li>
A fun and ambitious growing environment with a culture that takes on important things, takes risks, and learns quickly.</li><li>
The ability to demonstrate creativity, innovation, and conscientiousness, and find joy in working together.</li><li>
A team of highly skilled, incredibly kind, and welcoming employees, every one of whom has something unique to offer.</li><li>
We know that the overall success of our business is a collaborative effort, and we strive to provide ongoing opportunities for our employees to learn and grow, both personally and professionally.</li><li>
Full-time employees are eligible to participate in our benefits package which includes Medical, Dental, Vision Insurance, Paid time off, Short- and Long-Term Disability, 401k match and more.</li></ul> 
We are an equal opportunity and affirmative action employer. We embrace diversity and are committed to creating an inclusive environment for all employees. Applicants will be considered for employment without regard to race, religion, gender, gender identity, sexual orientation, national origin, age, disability, or veteran status.
2lXGu4dNqn</div>

Analytics Engineer, Care Operations

Netflix

<div>At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what&rsquo;s next.
Data Science and Engineering (&lsquo;DSE&rsquo;) at Netflix is aimed at using data, analytics, and sciences to improve various aspects of our business. We are looking for a Senior Analytics Engineer to join our New Content Experiences DSE team.
The New Content Experiences team focuses on introducing new content types and innovative experiences to our product. We partner closely with Product, Design, Algorithms, Content, and Engineering to surface opportunities, influence the product strategy, and evaluate the success of different initiatives. The most recently launched example of a New Content Experience is our Live offering (including WWE and the NFL Christmas games among other great hits!).
As part of a team of Data Scientists and Analytics Engineers, you will lead end-to-end product analytics for the space, which is key to a successful New Content Experiences ecosystem.
This role will partner closely with our stakeholders from Product and Technology to do advanced analytics that will inform the product, design, and engineering strategies to support the development and performance of our New Content Experiences portfolio. As an early member of the team, you will also help shape our overall Data Strategy, monitoring, and decision frameworks.
In this role, you will:
<ul><li>Partner directly with our stakeholders (e.g., Data Scientists, Product Managers, Designers, Engineers) on data, metrics &amp; analytics initiatives
</li><li>Lead end-to-end development of analysis and tools used by your direct stakeholders and a diverse set of teams across the company
</li><li>Responsible for analyzing and interpreting data to provide valuable insights and recommendations to enhance the member experience and improve product performance
</li><li>Collaborate with the data engineering and data science teams to ensure data quality, integrity, and availability for analysis
</li><li>Drive the direction and execution of your work, which spans from developing scrappy analysis and tools to designing scalable systems
</li></ul>We are looking for:
<ul><li>Exceptional communication and collaboration skills coupled with strong business curiosity and acumen
</li><li>5+ years of industry experience in a data analytics or data science function
</li><li>5+ years of experience in leveraging technical skills in manipulating large data sets with complex SQL and Python (or similar languages), big data technologies (e.g., Hadoop, Spark), and visualization tools
</li><li>Comfort with ambiguity; able to take ownership, and thrive with minimal oversight and process
</li><li>Experience managing stakeholders' asks, expectations, and relationships across a variety of stakeholders 
</li></ul>Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $330,000.00 - $566,000.00. This compensation range will vary based on location.
Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here .
Netflix is a unique culture and environment. Learn more here .
Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.
We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
Job is open for no less than 7 days and will be removed when the position is filled.</div>

Analytics Engineer 5 - New Content Experiences DSE

MUFG

<div>Do you want your voice heard and your actions to count?
Discover your opportunity with Mitsubishi UFJ Financial Group (MUFG), one of the world&rsquo;s leading financial groups. Across the globe, we&rsquo;re 150,000 colleagues, striving to make a difference for every client, organization, and community we serve. We stand for our values, building long-term relationships, serving society, and fostering shared and sustainable growth for a better world.
With a vision to be the world&rsquo;s most trusted financial group, it&rsquo;s part of our culture to put people first, listen to new and diverse ideas and collaborate toward greater innovation, speed and agility. This means investing in talent, technologies, and tools that empower you to own your career.
Join MUFG, where being inspired is expected and making a meaningful impact is rewarded.
The selected colleague will work at an MUFG office or client sites four days per week and work remotely one day. A member of our recruitment team will provide more details.
The Data Management Engineering organization is executing a product‑centric data strategy to deliver trusted, business‑aligned data products that power analytics, AI enablement, and critical decisioning across the enterprise. The organization partners closely with business, technology, and other stakeholders to ensure data assets are governed, scalable, and fit for regulatory and operational use across business domains.
The Vice President, Data Products &amp; Analytics Engineer is a senior individual‑contributor reporting to the Head of Data Management Engineering. This role has broad responsibility for shaping data product strategy, assessing business requirements, defining solutions, and ensuring consistent standards across multiple data product initiatives. This role demands strong influence across business and technology organizations, with regular interaction with senior leaders to align data product roadmaps, platform architecture, and engineering execution to enterprise priorities and measurable business outcomes.
Responsibilities for Data Products &amp; Analytics Engineer:
<ul><li>Develop and maintain strong, trust-based relationships with key stakeholders to understand their business challenges and identify how data solutions can support their objectives.
</li><li>Empower business and corporate functions with robust data capabilities, ensuring clear lineage to products, services, and business processes, providing valuable data insights within the business context, and facilitating seamless data access.
</li><li>Optimize data product lifecycle management to drive modernization and value from our data assets. Identify process and procedural optimizations to advance data governance, management, and use.
</li><li>Proactively engage with data users to drive data maturity, adoption, and self-service. Facilitate a culture of continuous improvement and data systems thinking.
</li><li>Partner with senior business stakeholders to understand strategic objectives and ensure data products enable analytics, reporting, and data consumption challenges.
</li><li>Contributes to the technical and product direction for a portfolio of well‑formed enterprise data products, translating complex business processes into curated, reusable, and governed data assets.
</li><li>Provide expertise on the end‑to‑end data product lifecycle, including data sourcing, design, engineering, quality, certification, and consumption readiness.
</li><li>Translate business and analytics requirements into clear data engineering specifications, and implementation plans. Apply modern data architecture patterns to enable scalable data consumption.
</li><li>Collaborate across engineering and analytics teams to promote common standards, tooling, and delivery practices in a matrixed environment.
</li><li>Enable advanced data consumption capabilities, including BI, self‑service analytics, and AI‑assisted querying under governed access controls.
</li><li>Contribute to data literacy and adoption by supporting documentation, data catalogs, and enablement of business data users.
</li></ul>Data Products &amp; Engineering Expertise
<ul><li>Demonstrated success modernizing data ecosystems through cloud‑based platforms, automation, and integrated data solutions that improve data quality, accessibility, governance, and enable advanced analytics and AI‑assisted data consumption.
</li><li>Proven ability to design, scale, and operate modern data architectures&mdash;including data marts, validation, and reconciliation frameworks&mdash;to enable end‑to‑end analytics and regulatory use cases.
</li><li>Strong hands‑on experience with cloud‑based data platforms and modern data architectures.
</li><li>Advanced SQL and strong experience with data transformation, profiling, validation, and reconciliation frameworks.
</li><li>Practical understanding of AI‑enabled data access patterns (semantic layers, natural language querying, curated retrieval) in regulated environments.
</li><li>Strong grounding in metadata management, lineage, data quality controls, and certification workflows.
</li><li>Experience in business, data, and application architecture and process re-engineering.
</li></ul>Leadership, Influence &amp; Business Acumen
<ul><li>Expertise in business requirements analysis, design, functional and detail design within the Banking &amp; Financial Services sector.
</li><li>Demonstrated ability to operate with senior‑level autonomy and influence across business, technology, and risk organizations.
</li><li>Strong executive communication skills, with the ability to explain complex technical concepts in clear business terms. Detail-oriented, but strategic in thinking with the ability to tell a story and sell a vision.
</li><li>Effective at building alignment, driving adoption, and managing competing priorities across a matrixed organization.
</li><li>Product‑oriented mindset with a balanced focus on near‑term delivery, risk management, and long‑term platform sustainability.
</li><li>Demonstrated ability to build consensus across business areas and other stakeholders to support new ways of thinking about capabilities.
</li><li>Ability to quickly transition as priorities change.
</li></ul>Technology &amp; Tooling
<ul><li>Expert knowledge of tools &amp; techniques including cloud platforms, programming languages, and modern software engineering practices.
</li><li>Cloud data platforms such as Snowflake and AWS‑based data services.
</li><li>Enterprise data governance and metadata platforms such as Collibra.
</li><li>Data Virtualization platforms such as Starburst.
</li><li>ETL Tools such as Informatica
</li><li>BI and analytics tools such as Tableau, PowerBI, Alteryx or equivalent platforms.
</li><li>Relational databases and enterprise data warehouse technologies.
</li><li>Agile delivery and collaboration tools including Jira and Confluence.
</li></ul>Qualifications
<ul><li>10+ years of data experience in the Banking &amp; Financial Services sector from a technology, data, and/or business operations perspective.
</li><li>10+ years of experience in data management and/or data product development.
</li><li>7+ years of experience in business, systems, and data architecture, and analysis.
</li><li>Proven experience as a Data Engineer and/or Business Data Architect or similar role, with a focus on business value creation and enablement.
</li><li>Bachelor&rsquo;s degree in science, business, management, or finance-related fields.
</li><li>Advanced degree is a plus.
</li></ul>The typical base pay range for this role is as follows:
<ul><li>New York / New Jersey: $184k-237k
</li><li>Non&ndash;New York / New Jersey: $153k-188k
</li></ul>depending on job-related knowledge, skills, experience and location. This role may also be eligible for certain discretionary performance-based bonus and/or incentive compensation. Additionally, our Total Rewards program provides colleagues with a competitive benefits package (in accordance with the eligibility requirements and respective terms of each) that includes comprehensive health and wellness benefits, retirement plans, educational assistance and training programs, income replacement for qualified employees with disabilities, paid maternity and parental bonding leave, and paid vacation, sick days, and holidays. For more information on our Total Rewards package,
Our hybrid work schedule is four days on-site and work remotely one day per week.
MUFG Benefits Summary
We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws (including (i) the San Francisco Fair Chance Ordinance, (ii) the City of Los Angeles&rsquo; Fair Chance Initiative for Hiring Ordinance, (iii) the Los Angeles County Fair Chance Ordinance, and (iv) the California Fair Chance Act) to the extent that (a) an applicant is not subject to a statutory disqualification pursuant to Section 3(a)(39) of the Securities and Exchange Act of 1934 or Section 8a(2) or 8a(3) of the Commodity Exchange Act, and (b) they do not conflict with the background screening requirements of the Financial Industry Regulatory Authority (FINRA) and the National Futures Association (NFA). The major responsibilities listed above are the material job duties of this role for which the Company reasonably believes that criminal history may have a direct, adverse and negative relationship potentially resulting in the withdrawal of conditional offer of employment, if any.
The above statements are intended to describe the general nature and level of work being performed. They are not intended to be construed as an exhaustive list of all responsibilities duties and skills required of personnel so classified.
We are proud to be an Equal Opportunity Employer and committed to leveraging the diverse backgrounds, perspectives and experience of our workforce to create opportunities for our colleagues and our business. We do not discriminate on the basis of race, color, national origin, religion, gender expression, gender identity, sex, age, ancestry, marital status, protected veteran and military status, disability, medical condition, sexual orientation, genetic information, or any other status of an individual or that individual&rsquo;s associates or relatives that is protected under applicable federal, state, or local law.</div>

Vice President, Data Products & Analytics Engineer

Pretium Packaging

<div>Grow boldly with Pretium and be a data and automation innovator!

About Us: Pretium Packaging, founded in 1992, is a leading supplier of injection-blow molded plastic containers, known for delivering superior quality, value, and customer service. With 20 manufacturing locations across North America, we provide innovative, high-performance packaging solutions to a diverse portfolio of brand owners in the U.S. and Canada.

We are looking for an Analytics Data Engineer to design, build, and maintain the curated data products that power reporting, analytics, and strategic decision-making across the organization. This role is responsible for transforming raw and operational data into trusted, business-ready datasets, semantic models, and analytical assets that enable self-service analytics and enterprise reporting. 
 
The Analytics Data Engineer owns the Silver, Gold, and Semantic layers of the analytics platform and serves as the bridge between foundational data engineering and business intelligence. Working closely with Data Engineers, BI Developers, Strategic Insights Analysts, and business stakeholders, this role ensures that data is governed, consistent, scalable, and aligned with business definitions and reporting requirements.

Remote location. 15% travel

What you&rsquo;ll own:
<ul>
<li>Analytics Engineering</li>
<li>Data Quality and Governance</li>
<li>Analytics Platform Support</li>
</ul>
What you&rsquo;ll bring:
<ul>
<li>5+ years of experience in analytics engineering, data engineering, business intelligence, or related disciplines.</li>
<li>Advanced SQL and data modeling expertise.</li>
<li>Oracle and IQMS a plus.</li>
<li>Experience designing dimensional models, semantic models, and analytical data products.</li>
<li>Strong understanding of medallion architecture concepts (Bronze, Silver, Gold).</li>
<li>Experience building and maintaining enterprise reporting datasets.</li>
<li>Ability to translate business requirements into scalable technical solutions.</li>
<li>Experience working with cross-functional business and analytics teams.</li>
<li>Strong communication, documentation, and problem-solving skills.</li>
</ul>
Equal Opportunity Employer 
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights (https://www.eeoc.gov/poster) notice from the Department of Labor.</div>

Sr Analytics Data Engineer

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