Data Ingestion Lead

Key Skills

Apache Kafka, Apache NiFi, Continuous Integration & Continuous Delivery - CI/CD, Data science techniques, DevOps, ETL/ELT technologies, Java Programming, Python Programming, Scala Programming

Job Description

Please list the most important and relevant responsibilities

• Mars Principles: Live and exemplify the Five Principles of Mars, Inc. within self and team.
• Data Ingestion and Processing: Manage the ingestion of data from various sources, ensuring data quality and integrity. Develop and optimize data pipelines to support real-time and batch processing. Implement best practices for data ingestion, storage, and processing.
• Quality and Compliance: Conduct regular audits and assessments to ensure data accuracy and security. Implement data quality checks and validations throughout the data lifecycle..
• Performance Metrics: Develop and track key performance metrics for data operations, providing regular reports and insights to stakeholders.
• Data Reliability: Ensure the reliability and availability of data assets, implementing backup and recovery strategies as needed to minimize downtime.
• Stakeholder Engagement: Collaborate with PN D&A teams, PN Architecture team, and segment data team to articulate the strategic value of data and advocate for investments in data capabilities and policies.
• Team and resource management: Hire, build, lead and manage multilocational teams covering data platforms, architecture, engineering, and governance throughout the development lifecycle, from ideation to ongoing optimization. Manage budget allocation.

Context and Scope

Explain how the job gets done and the way it operates within the team and with stakeholders

As part of Digital First, a new role has been created to build the foundational data capabilities that will power all our analytics products and create transformational business impact for the Pet Nutrition Division. This role encompasses the day-to-day operations of the data organization, including data acquisition, ingestion, transformation processes, and platform operations that support the business goals and analytics needs of the Pet Nutrition segment. This role will collaborate closely with cross-functional teams including product management, data strategy and governance, architecture, engineering, data science, and business intelligence. The role serves as part of the global digital organization focused on enabling data-driven decision-making. This role will also collaborate with and influence other D&A and Digital Technologies leaders across Mars to align on data standards, best practices, and emerging technologies.

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

• Bachelor’s/Master’s/higher in computer science, data science, engineering, mathematics, or related field

Knowledge / Experience

• 8+ years of experience in data management, with a focus on data acquisition, ingestion, and platform operations in a complex environment, preferably in the CPG or retail industry.
• Proficiency in data integration tools and technologies, such as ETL/ELT processes and APIs.
• Strong understanding of data quality assurance principles and practices.
• Proficiency in designing and implementing data ingestion pipelines using tools such as Apache Kafka, Apache NiFi, or similar technologies.
• Strong programming skills in languages such as Python, Java, or Scala, with experience in data processing frameworks like Apache Spark.
• A strong customer-centric mindset especially within an internal customer base with the purpose of driving adoption and use.
• Ability to engage and manage large diverse multi-locational teams (internal as well as vendors).
• Familiarity with Microsoft Azure tech stack, including but not limited to Azure Data Factory, Synapse Analytics, Databricks, Azure DevOps (CI/CD), Security Center, AZ Monitor, Azure Kubernetes Service (AKS), AzureML, and Purview would be advantageous.