LD&T Data Engineer
$73.4k - $122.85kPepsiCo Deutschland GmbH
Overview At PepsiCo, you’ll discover a place where our mission is to create smiles around the world. With a portfolio of more than 500 beloved brands including Gatorade, Lay’s and Quaker, our work touches millions of people every day. At the heart of the company is a team of thinkers, creators, and problem-solvers who collaborate to innovate and turn ideas into action. Driven by innovation and a focus on creating joyful moments through food and drinks, our decisions are guided by consumer centricity, creating opportunities for our associates to do meaningful work and make a lasting impact in the communities we serve. Whatever your role, you’ll be part of a global community that values your ideas and empowers you to make an impact on your career and on the world around you. Responsibilities We are seeking a highly skilled Data Engineer with a strong technical foundation to design, build, and optimize the data infrastructure that powers business insights and automation across the organization. In this role, you will develop and maintain robust ETL/ELT pipelines, transform raw data into clean and reliable datasets, and enable self-service analytics for stakeholders. You will work extensively with SQL and Python to extract, clean, and model large volumes of data, while leveraging cloud platforms to build scalable, cost-efficient solutions. The ideal candidate is passionate about data quality, thrives on automating manual processes through RPA and scripting, and enjoys partnering with business teams to translate their needs into actionable dashboards and reports using tools such as Power BI and Tableau. This is a hands‑on, technically focused position for someone who is comfortable owning the full data lifecycle, from ingestion and cleaning through to modeling, automation, and visualization. Design, develop, and maintain scalable ETL/ELT pipelines to ingest data from diverse source systems into cloud data warehouses and lakes. Write, optimize, and troubleshoot complex SQL queries and Python scripts to extract, clean, transform, and model large datasets. Perform data cleaning, validation, and quality checks to ensure the accuracy, consistency, and reliability of downstream reporting and analytics. Build and maintain automated workflows using RPA tools and scripting to streamline repetitive business processes and reduce manual effort. Deploy and manage data solutions on cloud platforms (e.g., Azure, AWS, or GCP), optimizing for performance, scalability, and cost. Develop and maintain interactive dashboards and reports in Power BI and/or Tableau to deliver actionable business insights. Collaborate with business stakeholders, analysts, and cross‑functional teams to gather requirements and translate them into technical solutions. Document data pipelines, data models, and processes, and follow best practices for version control, testing, and monitoring. Compensation and Benefits: The expected compensation range for this position is between $73,400 - $122,850. Location, confirmed job‑related skills, experience, and education will be considered in setting actual starting salary. Your recruiter can share more about the specific salary range during the hiring process. Bonus based on performance and eligibility target payout is 5% of annual salary paid out annually. Paid time off subject to eligibility, including paid parental leave, vacation, sick, and bereavement. In addition to salary, PepsiCo offers a comprehensive benefits package to support our employees and their families, subject to elections and eligibility: Medical, Dental, Vision, Disability, Health, and Dependent Care Reimbursement Accounts, Employee Assistance Program (EAP), Insurance (Accident, Group Legal, Life), Defined Contribution Retirement Plan. Qualifications Bachelor's degree (required) in Computer Science, Information Systems, Engineering, Data Science, or a related field, or equivalent practical experience. 3+ years of experience in data engineering, data warehousing, or a similar technical data role. Strong proficiency in SQL, including query optimization, stored procedures, and working with large relational datasets. Hands‑on programming experience with Python for data extraction, cleaning, transformation, and automation. Proven experience building and maintaining ETL/ELT pipelines and working with data integration tools. Experience with cloud platforms such as Azure, AWS, or GCP and their core data services. Experience automating business processes using RPA tools (e.g., UiPath, Power Automate, Automation Anywhere) and/or Python scripting. Proficiency in data visualization tools such as Power BI and/or Tableau, including building interactive dashboards and reports. Strong understanding of data modeling, data warehousing concepts, and data quality best practices. Excellent analytical, problem‑solving, and communication skills, with the ability to collaborate effectively with technical and business stakeholders. EEO Statement Our Company will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the Fair Credit Reporting Act, and all other applicable laws, including but not limited to, San Francisco Police Code Sections 4901-4919, commonly referred to as the San Francisco Fair Chance Ordinance; and Chapter XVII, Article 9 of the Los Angeles Municipal Code, commonly referred to as the Fair Chance Initiative for Hiring Ordinance. All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. PepsiCo is an Equal Opportunity Employer: Female / Minority / Disability / Protected Veteran / Sexual Orientation / Gender Identity / Age If you'd like more information about your EEO rights as an applicant under the law, please download the available EEO is the Law & EEO is the Law Supplement documents. View PepsiCo EEO Policy. Please view our Pay Transparency Statement. #J-18808-Ljbffr PepsiCo Deutschland GmbH
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