Digital Green Data Engineer (Senior Software Engineer) in Bangalore, India
Digital Green is looking for a savvy Data Engineer to join our growing technology team. The data engineer will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our software developers, data analysts, community developer partners on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our data architecture to support our next generation of products and data initiatives.
Technology at Digital Green
We are a multidisciplinary team that unites front and back end engineering with data, human centered design and product management.
We emphasise on rapid prototyping and piloting in close collaboration with our program teams to figure out what actually works and then figure out how to engineer solutions that work reliably and at scale in challenging environments with sporadic connectivity and emerging technology literacy, etc. We release our code for others to contribute and benefit. We are Empathetic and inclusive in our design that enables those most in need to capitalize on the promise of new technologies
Some of the problems we are working on right now:
How can data from disparate sources like IoT sensors, satellite imagery, hyperlocal weather stations and government databases be combined to generate targeted, contextual relevant advisories for farmers?
What are the most effective communication channels for reaching smallholder farmers around the world? Smartphone penetration and data connectivity continues to increase so this is dynamic and highly variable by geography. Messaging apps like whatsapp and telegram, IVR, mobile apps.
How can AI and NLP be applied to create vernacular language voice recognition that promotes inclusivity and extends the value of technology to groups typically left behind including women>
How can we apply machine learning and other advanced data analysis techniques to generate insights that enable smallholder farmers to increase their income?
How do we generate and manage data in a manner that is not extractive or exploitive but puts agency and control in the hands of farmers?
Create, optimize and maintain data pipelines,
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Create data tools for analytics and data integration to assist in analysing and integration with external data systems
Work with data and analytics experts to strive for greater functionality in our data systems.
Advanced working knowledge of SQL and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
Strong analytic skills related to working with unstructured datasets.
Build processes supporting data transformation, data structures, metadata, dependency, data integration and workload management.
A successful history of manipulating, processing and extracting value from large disconnected datasets.
Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
Experience supporting and working with cross-functional teams in a dynamic environment.
We are looking for someone with 4+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
Experience with big data tools: Hadoop, Spark, Kafka, etc.
Experience with relational SQL and NoSQL databases, including but not limited to MySQL, Postgres, MongoDB and Cassandra.
Experience with data pipeline, queuein and workflow management tools: RabbitMQ, Airflow etc.,.
Experience with AWS cloud services: EC2, RDS
Experience with stream-processing systems: Storm, Spark-Streaming, etc.
Experience with object-oriented/object function scripting languages: Python, Java, Scala, etc.
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