Data Engineer

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

One Demand Data & Analytics (ODDA) is a Mars Wrigley program that harnesses the power of data and insights to solve some of the critical business-wide problems we face – unlocking quality growth and operational excellence.

Through ODDA, we deliver connected insights across the entire demand ecosystem. We empower our Associates with the right data, tools and capabilities so they can take decisive action, maximizing value and making a meaningful impact on our consumers, our customers and our business.

What are we looking for

• Master’s Degree in Computer science, application programming, software development, information systems, database administration, mathematics, engineering, or other related field
• 6+ years in a rapid development environment, preferably within an analytics environment
• Demonstrated ability to be work with internal (Operations) and external (IT) stakeholders
• Must be able to interact and collaborate at all levels within Operations Analysis & Performance, OCC, cross-divisional working groups, and outside entities
• Experience with increasing code quality and implementing best practices across teams
• Advanced technical skills in the following areas:
• Proficiency in SQL (CTE, window functions, temporal data), SAP HANA experience is a large plus
• Proficiency in a scripting language (Python preferred)
• Proficiency of API Consumption
• Proficiency in ETL tooling (such as Informatica)
• Proven expertise in SAP ECC and SAP APO is a big plus
• Excellent communication skills and ability to present concepts to non-technical audience 
• Must be able to interact and collaborate at all levels within Operations Analysis & Performance, OCC, cross-divisional working groups, and outside entities
• Strong project management, organizational, and prioritizations skills
• 2 to 4 years' experience in applied data science role or equivalent; ideally in a CPG, Retail
• Knowledge and experience in modelling techniques and advanced applied skills (e.g. significance testing, GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.) using tools like Spark, Scala, SAS, R, Python, Bayesia, H2O, Storm, Yarn, and Kafka
• Experience querying databases (SQL, Hive)
• Experience working with big data platforms such as Hadoop ecosystem (Azure), including in-memory solutions (SAP HANA and Apache Spark)
• Working knowledge of data visualization tools such as Tableau, Power BI, D3, ggplot, to deliver output to the broader business community to improve decision making and productivity

What will be your key responsibilities?

• Design, develop, optimize, and maintain data architecture and pipelines that adhere to ELT principles and business goals
• Solve complex data problems to deliver insights that helps business to achieve goals
• Create data products for engineer, analyst, and data scientist team members to improve their productivity
• Advise, consult, mentor and coach other data and analytic professionals on data standards and practices
• Foster a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions
• Define and execute the Analytics Data Engineering roadmap (and work with enterprise BI to enhance the data lake and a real-time reporting environment for operations)
• Lead complex process improvement and project management engagements for both individual business units and cross-divisional initiatives
• Lead the evaluation, implementation and deployment of emerging tools and process for analytic data engineering in order to improve productivity as a team
• Develop and deliver communication and education plans on analytic data engineering capabilities, standards, and processes
• Partner with machine learning engineers, BI, and solutions architects to develop technical architectures for strategic enterprise projects and initiatives.
• Mentor junior members in technical proficiency and business acumen
• Learn about machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics
• Interface with business unit leaders to develop and maintain internal customer relationships