Responsibilities

• Create and maintain optimal data pipeline architecture,

• Assemble large, complex data sets that meet functional / non-functional business requirements.

• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and other ‘big data’ technologies like Databricks/Dremio/Snowflake/Airflow etc.

• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.

• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.

• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.

• Work with data and analytics experts to strive for greater functionality in our data systems.

• Utilizes available programming methodologies and languages and adhere to coding standards, procedures and techniques

Basic Qualifications:

• BS degree in Computer Science or equivalent with 2-6 years of IT practical experience.

• Ability to work and define best practices in collaboration with Agile Development teams

• Hands-on development and programming experience on any Object Oriented Programming Language such as Python or Pyspark.

• Knowledge of Micro-services architecture, design and business processes

• Hands-on experience technologies such as SQL (MySQL, MS SQL or Oracle), No-SQL (ex. Cassandra, Dynamo DB)

• Knowledge on data streaming, messaging and event driven systems such as Kafka, Azure events, Azure Streaming services

• Excellent verbal and written communication skills are required for the role

• Willingness to learn new skills and functionalities and adopt to challenges

Technical Skills

• Languages (Mandatory): Python

• Databases (Mandatory): SQL Server, PL/SQL, DB Design, ETL

• Cloud (Mandatory): Azure or AWS or Google

• Data Engineering (Optional): PySpark,  , Airflow , Dremio

• Devops (Optional): CI /CD , Azure Devops

• Backend (Optional):  Webservice