Job Details
What you will do
Develop solutions for Epsilon that will deliver high quality personalized recommendations across different channels to our customers
Working with Data science team to ensure seamless integration and support of machine learning models.
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.
Develop end-to-end (Data/Dev/MLOps) pipelines based on in-depth understanding of cloud platforms, AI/ML lifecycle, and business problems to ensure solutions are delivered efficiently and sustainably.
Collaborate with other members of the team to ensure high quality deliverables
Learning and implementing the latest design patterns in software engineering
Data Management
Experience with both structured and unstructured data, and Hadoop, Apache Spark, or similar technologies
Good understanding of Data Modeling, Data Warehouse, Data Catalog concepts and tools
Experience with Data Lake architectures, and with combining structured and unstructured data into unified representations
Able to identify, join, explore, and examine data from multiple disparate sources and formats
Ability to reduce large quantities of unstructured or formless data and get it into a form in which it can be analyzed
Ability to deal with data imperfections such as missing values, outliers, inconsistent formatting, etc.
Ability to manipulate large datasets, (millions of rows, thousands of variables)
Software Development
Ability to write code in programming languages such as Python/NodeJs, PySpark and shell script on Linux
Familiarity with software development methodology such as Agile/Scrum
Love to learn new technologies, keep abreast of the latest technologies within the cloud architecture, and drive your organization to adapt to emerging best practices
Architecture and Infrastructure
Architectural design experience on AWS.
Experience in delivering software with AWS EC2, S3, EMR/Glue, Lambda, Data Pipeline, CloudFormation, Redshift etc.
Good knowledge of working in UNIX/LINUX systems
Qualifications
Bachelor?s Degree in Engineering and related field with 2+ years of similar experience
Tech Stack: Python, PySpark, Micro services, Docker, Serverless Frameworks.
Hands on experience building ETL workflows/pipelines
Experience in relational and non-relational databases and SQL (NoSQL is a plus).
Experience with Cloud technologies (AWS or Azure)
Experience building Data and CI/CD/MLOps pipelines
Familiarity with Airflow and MLFlow tools
Familiarity with automated unit/integration test frameworks
Experience working on AdTech or MarTech technologies is added advantage
Knowledge of machine learning algorithms and concepts and implementation will be a plus
Good written and spoken communication skills, team player.
Strong analytic thought process and ability to interpret findings