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Mars

Data Engineering Lead - Growth

Posted 22 Days Ago
Remote
8 Locations
Senior level
Remote
8 Locations
Senior level
The DDF Engineering Lead will oversee a team of data engineers and DevOps engineers, driving the delivery of data products and implementing DataOps practices. Responsibilities include collaborating with cross-functional teams, optimizing data pipelines, ensuring adherence to governance policies, and promoting data quality. This role requires significant technical leadership and stakeholder engagement to maximize data utilization for business value.
The summary above was generated by AI

Job Description:

Are you passionate about Data and Analytics (D&A) and excited about how it can completely transform the way an enterprise works? Do you have the strategic vision, technical expertise, and leadership skills to drive data-driven solutions? Do you want to work in a dynamic, fast-growing category? If so, you might be the ideal candidate for the role of Senior Director, Data Foundations, in the Data and Analytics function for Global Pet Nutrition (PN) at Mars.

Pet Nutrition (PN) is the most vibrant category in the FMCG sector. As we work to transform this exciting category, a new program, Digital First, has been mobilized by the Mars Pet Nutrition (PN) leadership team. Digital First places pet parents at the center of all we do in Mars PN, while digitalizing a wide range of business process areas, and creating future fit capabilities to achieve ambitious targets in top line growth, earnings, and pet parent centricity. The Digital First agenda requires Digitizing at scale and requires you to demonstrate significant thought leadership, quality decision making, deep technical know-how, and an ability to navigate complex business challenges while building and leading a team of world class data and analytics leaders.

With Digital First, PN is moving to a Product based model to create business facing digital capabilities. Develop and maintain robust data pipelines and storage solutions to support data analytics and machine learning initiatives. Reporting to the Director-Data engineering solution, The role operates globally in collaboration with teams across core and growth functions

Key Responsibilities

Please list the most important and relevant responsibilities

Leadership and Team Management: Lead and mentor a team of data engineers and DevOps engineers. Provide guidance and support in the design, implementation, and maintenance of data assets. Foster a collaborative and high-performance team culture focused on innovation and excellence Data Asset Delivery: Drive the end-to-end delivery of data products. Collaborate closely with cross-functional teams to understand business requirements and translate them into technical solutions. Ensure timely and accurate delivery of data products that meet business needs and quality standards. DataOps and Optimization: Implement DataOps practices to streamline data engineering workflows and improve operational efficiency. Automate data pipeline deployment and monitoring using CI/CD tools. Technical Leadership: Provide technical leadership and guidance on data engineering best practices. Stay informed about industry trends and emerging technologies in data engineering and analytics.   Standardization and Governance: Ensure adherence to data governance policies, procedures, and standards. Implement best practices for data management, security, and compliance. Promote data quality and integrity across all data products. Monitor data pipeline performance and optimize for scalability, reliability, and speed. Stakeholder Engagement: Collaborate with PN D&A leadership, PN product owners, and segment D&A leadership to synchronize and formulate data priorities aimed at maximizing value through data utilization.

Job Specifications/Qualifications

State the preferred education, knowledge, skills and experience this position requires. State the physical and/or mental requirements for the role (e.g. stand for x hours, lift x weight, concentration on repetitive tasks).

Note: May differ from the current job holder’s own skills and experience.

Education & Professional Qualifications

  • 8+ years’ experience as a Data Engineer.

Knowledge / Experience

  • Experience with Spark, Databricks, or similar data processing tools.
  • Strong technical proficiency in data modeling, SQL, NoSQL databases, and data warehousing.
  • Hands-on experience with data pipeline development, ETL processes, and big data technologies (e.g., Hadoop, Spark, Kafka).
  • Proficiency in cloud platforms such as AWS, Azure, or Google Cloud, and cloud-based data services (e.g., AWS Redshift, Azure Synapse Analytics, Google BigQuery).
  • Experience with DataOps practices and tools, including CI/CD for data pipelines.
  • Excellent leadership, communication, and interpersonal skills, with the ability to collaborate effectively with diverse teams and stakeholders.
  • Strong analytical and problem-solving skills, with a focus on driving actionable insights from complex data sets.
  • Experience with data visualization tools (e.g., PowerBI).
  • Proficiency in Microsoft Azure cloud technologies would be a bonus.

Key Mars Leadership Competencies (4-6)

Refer to the Mars Talent and Development Library

Note: competencies selected should be job related

  • Communicates effectively
  • Collaborates
  • Drives Results
  • Self-Development

Key Functional Competencies & Technical Skills (3-5)

Refer to the Mars Talent and Development Library

Distinguish any preferred competences at the end of the list & notate them as “preferred”

  • Data Modeling: Expertise in conceptual, logical, and physical data modeling, with an emphasis on designing scalable and efficient data structures.
  • ETL Development: Proficiency in building and maintaining ETL processes, including data ingestion, transformation, and integration.
  • Cloud Platforms: Proficiency in using cloud platforms like AWS, Azure, or Google Cloud for data storage, processing, and analytics.
  • Database Management: Strong knowledge of both relational and non-relational database systems, including SQL and NoSQL databases.
  • DataOps Practices: Experience with CI/CD for data pipelines and automating data engineering workflows to improve efficiency and reliability.
  • Data Governance: Understanding of data governance principles, including data quality, metadata management, and regulatory compliance.

#TBDDT

Mars is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. If you need assistance or an accommodation during the application process because of a disability, it is available upon request. The company is pleased to provide such assistance, and no applicant will be penalized as a result of such a request.

Top Skills

Data Analytics
Data Engineering
DevOps
Machine Learning

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