Title: Senior Engineer - Distribution Operations Location: Detroit United States Job Description: DTE is one of the nation's largest diversified energy companies. Our electric and gas companies have fueled our customer's homes and Michigan's progress for more than a century. And as Michigan's largest source of renewable energy, we're creating a cleaner, healthier environment to power our future. We're also serving communities beyond Michigan, where our affiliated businesses offer renewable energy, emission control technologies, and energy services to industries in 19 states. But we're more than a leading energy company... and working at DTE is more than just a job. At DTE, we take great care of each other and our customers, and we use our energy to be a force for growth and prosperity in our communities. When you join us, you'll be part of a team that welcomes, recognizes, and celebrates differences and values everyone's health, safety, and wellbeing. Are you ready to make that kind of difference? Bring your energy to DTE. Together, we can achieve great things. Testing Required: Not Applicable Employment Sponsorship: This position is not eligible for visa sponsorship currently. Hybrid Role: This role is hybrid, with an established schedule of in-person work required at an assigned work location. Any remote work is expected to be performed from an employee's primary residence, unless allowed (or prohibited) through the Company's remote work guidelines. Emergency Response: Yes - Must be available to perform a primary assignment in support of DTE's emergency response to storms or other events that impact service to our customers. Job Summary Senior level engineer responsible for planning and conducting engineering activities. Requires the use of advanced techniques and the application of theories, precepts, practice and disciplines, including practical field experience. Incumbents have the responsibility and authority to make decisions on engineering problems and methods applicable to the resolution of important issues. Participates on and leads teams of field employees, technicians, engineers and other personnel. Key Accountabilities - Develops, coordinates, and directs important projects or field engineering assignments with complex features. - Performs assigned (or initiates) engineering studies, proposing solutions to engineering-related problems; develops models and analyzes data to support improvement programs, techniques & solutions. - Interfaces with outside departments, vendors, suppliers, and reliability entities. - Develops or assists in presentations of engineering-related projects to all levels of management & external parties (contractors, customers, etc.). - Plans and manages group workflow to meet budgets and schedules. - May mentor and provide guidance/direction for less experienced staff. Minimum Education & Experience Requirements - Bachelor's Degree in Engineering or Engineering Technology and a minimum of 4 years of job relevant experience Other Qualifications Preferred - Master's Degree in Engineering or job relevant discipline - Industrial Engineer or Continuous Improvement Experience (Green Belt) Other Requirements - Proficiency in Microsoft Office programs, primarily Excel and Word - Strong analytical and problem solving skills - Strong time management, prioritization, and organization skills - Proficient communication and interpersonal skills Additional Information Incumbents may engage in all or some combination of the activities and accountabilities, and utilize a variety of the competencies cited in this description depending upon the organization and role to which they are assigned. This description is intended to describe the general nature and level of work performed by incumbents in this job. It is not intended as an all-inclusive list of accountabilities or responsibilities, nor is it intended to limit the rights of supervisors or management representatives to assign, direct and control the work of employees under their supervision. PRIVACY NOTICE TO CALIFORNIA JOB APPLICANTS At DTE Energy, we are committed to providing an inclusive workplace where everyone feels welcome and a sense of belonging. We seek individuals with a heart for service, a passion to help our communities prosper, and ideas to help shape the future of energy. We are proud to be an equal opportunity, employer that considers all qualified applicants without regard to race, color, sex, sexual orientation, gender identity, age, religion, disability, national origin, citizenship, height, weight, genetic information, marital status, pregnancy, protected veteran status or any other status protected by applicable federal and/or state laws.

Ready to do the most impactful work of your career? At Coinbase, we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase. Analytics Engineer The Compliance Data team, part of Coinbase's Platform organization, builds the trusted, certified data foundations that every regulatory obligation at Coinbase depends on. At the center of our work is the Compliance Data Mart (CDM), Coinbase's canonical source of truth for user, transaction, and compliance data. As an Analytics Engineer, you'll design, build, and maintain the production-grade data models and pipelines that downstream regulatory reporting, analytics, and AI workflows all build on. This is a hybrid role blending data engineering discipline with analytical instincts - you'll build durable foundations while also supporting live regulatory exams, audits, and time-sensitive data requests when regulators come calling. What you'll do: - Design, build, and maintain the production-grade data models and pipelines at the core of the CDM, covering user, transaction, and compliance data across retail and institutional product lines, owning the full lifecycle from architecture through deployment and maintenance. - Build data quality checks, data contracts, validation logic, and monitoring that protect the integrity of the foundations before issues propagate into regulatory reports or downstream workflows. - Partner with upstream engineering teams to fix data gaps and absorb product changes at the source, taking accountability for data issues anywhere in the stack rather than passing them downstream. - Support live regulatory exams, audits, and ad hoc regulator requests with accurate, timely data, balancing deadline-driven reactive work with long-term foundational projects. - Automate recurring manual workflows into scalable pipelines and self-serve tooling, building durable infrastructure that enables downstream teams and AI agents to answer their own questions. - Perform front-line on-call duties, triage pipeline incidents, contribute to root cause analysis, and maintain clear technical documentation and runbooks. Required Skills and Experience: - 2+ years of experience building and maintaining production data pipelines and data models, with daily proficiency in SQL, Python (scripting, automation, OOP), dbt, Airflow, and modern warehouse architecture (Snowflake or Databricks). - Demonstrated experience with data modeling patterns (star/snowflake schemas, OBTs, SCDs) and building certified or canonical data models that serve multiple downstream consumers. - Track record implementing data quality frameworks including data contracts, validation logic, reconciliation, and monitoring to catch issues before they reach downstream reports. - Experience supporting time-sensitive, high-stakes data needs (regulatory exams, audits, or financial reporting) while maintaining accuracy standards under pressure. - Proven ability to work independently, scoping and driving foundational data work end-to-end without waiting for direction, and converting tribal knowledge into durable, documented infrastructure. - Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality. Job #: P76808 Pay Transparency Notice: The target annual base salary for this position can range as detailed below. Total compensation may also include equity and bonus eligibility and benefits (including medical, dental, and vision). Annual base salary range (excluding equity and bonus): €122.900—€122.900 EUR - Application Limit: Candidates may submit a maximum of 4 applications per 30-day period. - Equal Opportunity Employer: Coinbase is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or genetic information. Applicants with criminal histories will be considered consistent with applicable federal, state, and local laws. - US Applicants: View Employee Rights, Know Your Rights, and E-Verify Notice of Participation. - Accommodations: If you are an individual with a disability who needs a reasonable accommodation, email us your request and contact info at accommodations[at]coinbase.com. Need screen reading technology? Click here to download a free compatible screen reader and view the tutorial. - Data Privacy & Arbitration: By submitting your application, you agree to our Candidate Privacy Notice. US applicants: By submitting your application, you agree to Arbitration of Disputes. - AI Disclosure: Coinbase is piloting an AI tool based on machine learning technologies to conduct initial screening interviews to qualified applicants. The tool simulates realistic interview scenarios and engages in dynamic conversation. Coinbase is also piloting an AI interview intelligence platform to transcribe and summarize interview notes, allowing our interviewers to fully focus on you as the candidate. Coinbase will not use AI to make decisions impacting employment.

• Design and build robust dbt models on Databricks that transform raw, ingested data into clean, conformed, and analytics-ready datasets. • Define and implement KPI logic in collaboration with business and analytics stakeholders, ensuring consistent definitions across domains. • Maintain and evolve the semantic/presentation layer, ensuring data products are reliable, tested, documented, and performant. • Apply software engineering best practices to analytics code: version control, testing, CI/CD, and documentation. • Independently onboard new data domains (e.g. marketing attribution, product usage, customer care, subscription data) with limited guidance — exploring the data, understanding its structure and meaning, and deciding how to best model it. • Proactively engage business partners and domain owners to understand context, validate assumptions, and align on KPI definitions. • Identify data quality issues early and work with the Data Management team to resolve them at source. • Act as the connective tissue between data engineers and analysts: translating analytical needs into engineering tasks, and surfacing data realities back to the business. • Work with the Analytics team to ensure the presentation layer meets reporting and self-service needs. • Contribute to data governance: naming conventions, lineage documentation, and model cataloguing. • Support the broader team in extending analytics coverage to new brands and domains over time.

Your role at DynatraceDynatrace’s Data & Analytics organization is focused on building a scalable, AI-ready, self-service data ecosystem across the company. As a Senior Analytics Engineer, you will play a key role in designing and delivering high-quality data products that support reporting, self-service analytics, and emerging AI use cases. This is a hands-on technical role for someone who excels at translating business needs into well-structured, reliable analytical data assets. You will work closely with business stakeholders, data engineers, platform engineers, and BI teams to develop trusted, scalable, and well-governed datasets. In addition, you bring awareness of modern AI-assisted development workflows, including tools such as GitHub Copilot or Claude, and are comfortable leveraging these to improve productivity, documentation, and data model design. You will contribute to advancing our data modeling practices and help ensure that our data products are consistent, reusable, and aligned with business goals. Key Responsibilities: Data Product Design & Development - Design and develop scalable analytical data models, curated datasets, conformed dimensions, and standardized metrics - Translate complex business requirements into clear, reliable, and reusable data products that support both executive reporting and day-to-day analytics use cases - Contribute to designing data models and metadata structures with AI readiness in mind, including column-level descriptions, consistent naming conventions, and well-documented semantic context - Build and maintain data structures that support discoverability and usability across analytics, BI, and emerging AI/ML use cases Standards, Quality & Governance - Follow and contribute to established standards and best practices for SQL development, dbt modeling, testing, documentation, and data quality - Support the implementation of the semantic layer by ensuring metric definitions and business logic are consistently applied - Implement and maintain data quality checks, governance standards, and security measures within dbt models and Snowflake - Help ensure data models are well-tested, documented, and aligned with business definitions Collaboration & Technical Contribution - Partner with data engineers, platform teams, governance, and business stakeholders to gather requirements and deliver data solutions - Collaborate with team members through code reviews, knowledge sharing, and adoption of best practices - Contribute to cross-functional initiatives focused on improving standardization, consistency, and reuse of analytics assets - Identify opportunities to improve processes, enhance automation, and streamline development workflows What will help you succeedRequired - Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field - 5–8+ years of experience in analytics engineering, data modeling, or related roles with strong focus on SQL programming - Strong SQL skills, including experience with complex analytical queries and performance optimization - Solid hands-on experience with dbt Cloud, including models, tests, and documentation practices - Experience working with Snowflake, including query tuning and understanding of warehouse performance - Strong understanding of dimensional modeling (Kimball) concepts including star schemas, conformed dimensions, and slowly changing dimensions - Experience working within established analytics engineering or data modeling frameworks and standards - Ability to work independently on complex tasks while collaborating effectively with cross-functional teams - Strong communication skills, with the ability to translate technical concepts for business stakeholders - Experience with data quality validation, testing approaches, and governance alignment - Proficiency with Git/GitHub workflows including pull requests and code reviews - Proven experience with AI-assisted development tools such as GitHub Copilot, Claude, or similar, and the ability to leverage them to improve productivity, development workflows, and documentation. - Experience or familiarity with Power BI, including understanding of downstream reporting needs and the ability to support or contribute to BI development when needed Preferred - Master’s degree in a related field - Python experience for automation, scripting, or data validation - Exposure to semantic layer concepts or metric frameworks (e.g., dbt Semantic Layer, Cube, AtScale) - Familiarity with AI/ML data readiness, feature engineering concepts, or designing data for downstream advanced analytics use cases - Experience with data ingestion tools such as Fivetran - Exposure to enterprise systems such as Salesforce, NetSuite, or SuccessFactors Why you will love being a Dynatracer - Dynatrace is a leader in unified observability and security. - We provide a culture of excellence with competitive compensation packages designed to recognize and reward performance. - Our employees work with the largest cloud providers, including AWS, Microsoft, and Google Cloud, and other leading partners worldwide to create strategic alliances. - You'll get to work at the forefront of innovation with Dynatrace Intelligence—the industry's first agentic operations system. Bringing together deterministic and agentic AI, it helps teams understand what's happening, why it matters, and what to do next— automatically. - Over 50% of the Fortune 100 companies are current customers of Dynatrace. Compensation and RewardsDue to legal reasons we are obliged to disclose the minimum salary for this position, which is €61,000 gross per year based on full-time employment (38.5 h / week). We offer a higher salary in line with qualifications and experience.