Sr. Data Engineer

We need to output HTML fragment with sections: headings

for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections where posting has real specific content. Must not repeat job title as heading. No Job ID etc. Remove boilerplate. Must preserve all substantive info. We need to parse the posting. Let's extract sections: - About the role / company description: The first paragraph about Premier Nutrition Company, purpose, culture, Great Place to Work, etc. That's about the company and role context. Could be "About the role" or "About the company". Use heading About the role. - Responsibilities: The bullet list under "Design, Develop, and Maintain Data Infrastructure and Pipelines: 60% of your time", "Enhance and Optimize DataOps Operational Excellence: of your time 30%", "Data Warehouse Administration: 10% of your time". Also earlier description: "As a Data Engineer, you will help our company solve their most challenging problems and drive decisions with data..." etc. So responsibilities include those. - Requirements: Education, Experience, etc. The "What are we looking for?" section includes Education, Experience, etc. Also "Preferred Qualifications". Could combine under Requirements or separate Qualifications. The instruction: use headings for Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we need to decide what goes where. We have Education, Experience, etc. That's likely Requirements. Preferred Qualifications could be Qualifications. Skills list is separate. Benefits: The posting mentions many benefits: Year-round ½ day Fridays, in-office massages, free lunches & snacks, dogs in the office, culture of belonging celebrations, engaging in-office events like bring your kids to work day, 6% 401k match after 1 year, generous paid family leave regardless of gender, all positions bonus-eligible, company-wide volunteer days, company-matched charitable donations, no employee handbook, no dress code, coaching conversations instead of performance reviews, and walking meetings. Also mention of gym with rock-climbing wall, café, free onsite parking, greenery, transportation options. Also hybrid work schedule: expected to come in Tuesday through Thursday if within 100 miles. Also mention of pay scale: $170k to $180k. Schedule: The hybrid work expectation: Tuesday through Thursday in-office, hybrid. Could be a Schedule section. Pay: The expected pay scale $170k-$180k. We must not include sections with placeholder like "commensurate with experience". Here we have actual numbers. We must not include boilerplate like EEO etc. We must not repeat job title as heading. We must output only HTML fragment. Let's craft sections:

About the role

with paragraph summarizing company purpose, culture, Great Place to Work, etc. Must preserve all substantive info; we can't summarize away detail? The instruction: "Preserve ALL substantive information; do NOT invent or summarize away detail." That means we need to keep details, not omit. But we can combine into paragraphs; we must not lose any substantive info. That's tricky: we need to include all details from the posting. However we can rephrase but must keep meaning. Probably acceptable to condense but not lose info. We'll try to keep key points. We need to include all details: company description, purpose, culture, Great Place to Work, Fortune ranking, benefits list, hybrid work schedule, office details, pay scale, responsibilities breakdown, education, experience, preferred qualifications, skills list, etc. We'll create sections: About the role: include company description, purpose, culture, Great Place to Work, Fortune ranking, etc. Responsibilities: include the three time allocations and detailed tasks. Requirements: include Education, Experience (5+ years, 7+ years SQL, programming, etc.) Qualifications: include Preferred Qualifications (Master's, BI tool, on-call, strategic thinking, CPG experience) Skills: include the list of skills/attributes. Benefits: include the list of perks and office amenities. Pay: include salary range. Schedule: include hybrid work expectation (Tuesday-Thursday in-office if within 100 miles) and maybe mention of hybrid workplace. We must not include any filler like "commensurate with experience". Not present. Let's craft HTML. We'll need to use

• for lists. We'll need to ensure we don't duplicate content. Let's draft. First, About the role paragraph: Premier Nutrition Company (PNC) is a fast‑growing proactive wellness company that makes Premier Protein and Dymatize brands and is part of BellRing Brands (NYSE: BRBR). Founded in 1997, its purpose is “Changing Lives with Good Energy.” The company emphasizes a purpose‑driven, autonomous workforce, a culture of belonging, and a regenerative culture that has earned it Great Place to Work™ certification for nine consecutive years (2025) and a top‑12 ranking on Fortune’s Best Workplaces list for seven straight years, currently #8 in its category. PNC offers many employee‑focused perks such as year‑round half‑day Fridays, in‑office massages, free lunches and snacks, dogs in the office, belonging celebrations, bring‑your‑kids‑to‑work events, a 6% 401k match after one year, gender‑neutral paid family leave, bonus‑eligible positions, company‑wide volunteer days, matched charitable donations, no employee handbook, no dress code, coaching conversations instead of performance reviews, and walking meetings. The new 133,000 sq ft headquarters in Emeryville, CA (opened early 2026) features spacious workspaces, a gym with a rock‑climbing wall, a café, free onsite parking, abundant greenery, and multiple transportation options. That seems to capture all. Now Responsibilities: We'll list bullet points. We have three time allocations: - Design, Develop, and Maintain Data Infrastructure and Pipelines (60% of time): * Design, build, and maintain cloud-native data pipelines and infrastructure to support analytics, reporting, and data science use cases in a SaaS‑based environment. * Perform all stages of the data lifecycle: requirements gathering, design, ingestion, transformation, modeling, testing, deployment, monitoring, and production support. * Implement and manage ELT pipelines using tools such as Fivetran, dbt, and Python, delivering reliable and scalable data solutions. * Develop and maintain data models, data marts, APIs, and automation scripts to streamline analytics workflows. * Design and deploy database schemas, tables, and views in Snowflake across multiple environments (DEV, QA/UAT, PROD). * Collaborate with stakeholders to translate business requirements into robust technical designs. * Support documentation, training, and enablement to drive adoption of enterprise data assets. - Enhance and Optimize DataOps Operational Excellence (30% of time): * Protect the data pipeline: monitor production schedule, troubleshoot failures, ensure smooth operation. * Monitor data quality and investigate problems. * Administer Snowflake security strategy and database management. * Fine‑tune and optimize databases, queries, and pipelines for improved performance and efficiency. * Proactively identify processes that would benefit from system automation to increase team effectiveness and operating efficiencies. * Research and test new technology solutions; assist in vetting architectural changes or database designs needed for enterprise adoption and assess impacts. - Data Warehouse Administration (10% of time): * Follow documented procedures for configuring, maintaining, upgrading, testing, and deploying as a database administrator. * Ensure best technical practices are followed for all enterprise database administration to provide the best user experience and sustainable design. Also earlier generic responsibilities: "As a Data Engineer, you will help our company solve their most challenging problems and drive decisions with data. As a member in our Enterprise Data Intelligence team, you will be at the center of data and analytical innovation and adoption. In this role, you will drive value by migrating, acquiring, maintaining, and evolving our data integration process and platform. Activities range from data acquisition and validation, designing and implementing ETL/ELT data pipelines, designing and implementing databases, job suite execution and monitoring, support testing, troubleshooting, and system analysis. You will be collaborating with all our departments to build end-to-end data infrastructure and pipelines that promote reporting and advanced analytics and further business process evaluation." We could incorporate that as introductory paragraph before the bullet list. We'll include a paragraph then the three subsections maybe as subheadings? But we only allowed

  for section headings; we could still use

  for intro and then

  for each bullet group. Could also use

  but not allowed. We'll just use

  intro then separate

  for each major responsibility group with a preceding

  describing the percentage. We'll need to preserve the percentages. We'll include them in the

  before each list. Now Requirements: Education and Experience. Education: Bachelor’s degree in computer science, Engineering, Information Systems, or related technical disciplines. Experience: - 5+ years of experience as a Data Engineer working within cloud-native and SaaS‑based environments, supporting enterprise data platforms built on data warehouses, data lakes, and application databases (e.g., Snowflake, Oracle, SQL Server). - 7+ years of SQL experience with proven ability to write, optimize, and maintain complex queries and stored procedures. - Programming experience in Python, Scala, or other scripting languages for automation, data transformation, and integration. - Hands‑on experience designing, building, and maintaining ELT/ETL data pipelines, dimensional models, and data marts using modern tools such as dbt, Fivetran, or equivalent cloud‑based frameworks. - Demonstrated experience working with SaaS data sources and APIs, integrating data from cloud‑based systems such as ERP (e.g., NetSuite), CRM, and planning tools (e.g., Oracle EPM, O9, or Salesforce). - Exposure to or hands‑on experience with AI/LLM frameworks (e.g., Snowflake Cortex, MCP, or similar technologies) to enhance automation and data intelligence. - Experience with data integration and orchestration tools (e.g., Dell Boomi, Airflow, Azure Data Factory, or equivalent). - Strong understanding of data governance, observability, lineage, and data quality management in a cloud environment. - Experience using Git‑based version control systems (e.g., GitHub, GitLab) and CI/CD workflows for deployment across multi‑environment pipelines (DEV, QA, PROD). - Working knowledge of cloud platforms (preferably Azure, with exposure to AWS or GCP) and secure data exchange mechanisms (APIs, SFTP). We'll put these in a

  . Now Qualifications (Preferred Qualifications): - Master’s degree in Computer Science, Engineering, Information Systems, or related technical disciplines preferred. - Hands‑on knowledge with at least one key BI market tool (Tableau, SAP BO, Oracle BI, MS Power BI) is a plus. - Must be willing to be on call for night/weekend production support. - Ability to think strategically about tools and technologies that enable analytics. - Experience working in CPG industry. Now Skills: list of skills/attributes. We'll create a
  with each skill. Skills list from posting: - Problem‑Solving: Ability to analyze complex data challenges and develop innovative solutions that align with business objectives. - Get Things Done: Great work ethic and moves with a sense of urgency. - Drives Continuous Improvement: Always focusing on effective and efficient work and ways to get better. - Obsesses over the Details and committed to paying attention to the details - Demonstrated excellent verbal/written communication skills. - Life long learner: A passion for staying up‑to‑date with the latest trends and advancements in data engineering and related technologies. - Provocative thinker who is courageous to share his or her thoughts regardless of the level of the audience - Self‑motivated individual who can identify issues/opportunities for improvement and be proactive in addressing