Job Description

About ADM:

We are one of the world’s largest nutrition companies and a global leader in human and animal nutrition. We unlock the power of nature to provide nourishing quality of life by transforming crops into ingredients and solutions for foods, beverages, supplements, livestock, aquaculture, and pets.

About ADM India Hub:

At ADM, we have long recognized the strength and potential of India’s talent pool, which is why we have maintained a presence in the country for more than 25 years. Building on this foundation, we have now established ADM India Hub, our first GCC in India.

At ADM India Hub, we are hiring for IT and finance roles across diverse technology and business functions. We stand at the intersection of global expertise and local excellence, enabling us to drive innovation and support our larger purpose of unlocking the power of nature to enrich quality of life.

Data Engineer

Summary:

The Data Engineer role will work on designing, building, and implementing data solutions to support strategic analytics projects & initiatives that drive strategic growth for ADM. This involves liaising with functional teams that generate or acquire data, with application owners to understand raw or source data structures, and end users to accurately design and build strategically significant Data centric projects.

Responsibilities:

Standardize data and reporting across businesses and teams to enhance the consistency and quality of data
Design, develop, test and document data integrations and assist with deployment, validation and hyper care processes
Maintain and support existing ETL/ELT integrations leveraging technical documentation
Develop and maintain existing codebases as needed
Assist with review to confirm technical feasibility of integration development objects based on integration principles and best practices
Understand and navigate a wide array of source data systems (enterprise data warehouses, relational databases, IT systems, in house and COTS applications, documents, APIs, unstructured data, big data, NoSQL databases, etc.)
Analyze data and assist with developing insights to enable business decision making
Developing prototypes and proof of concepts for required solutions
Contribute to high level solution/project design
Document solutions through high/low level design documentation
Synthesize & communicate ideas and recommendations to colleagues and management
Recommend solutions to address gaps in current data processes
Assist with project development estimation (epics, stories, features, bugs)
Supervise and review activities of external project partners

Requirements for this position include:

Bachelor’s degree in business Analytics, Statistics, Computer Science or related field
2-5 years of experience performing data mining, data analytics and predictive modeling initiatives
Significant SQL Scripting / TSQL development experience
Significant Experience in at least one other programming language (Python, Java, Scala)
Proven data processing (ETL/ELT), data mining, data analytics and predictive modeling abilities
OLAP & OLTP database development experience with relational databases like MSSQL Server/Oracle & Postgres
Understanding of data warehousing and data mart concepts
Azure Cloud experience (Administration, Data engineering & Networking)
Experience with pipelining tools (ADF/Azure Synapse/Databricks Pipelines preferred)
Experience with MPP systems, Azure Synapse/Databricks preferred
Familiarity with supervised and unsupervised machine learning techniques
Experience of working within an Agile development framework
Unit & Integration testing experience (concepts such as TDD) and experience of frameworks (such as SSDT, Pytest)
DevOps implementation/execution experience (source control, CI/CD, release environment management)
Ability to develop and solution both independently and collaboratively a necessity

Preferred additional experience:

Salesforce Integration experience (e.g. adf salesforce bulk api)
PowerShell Core development.
Understanding of GenAI fundamentals (i.e. Retrieval Augmented Generation, embeddings, direct and indirect search methods).